{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/transformer"},"x-facet":{"type":"skill","slug":"transformer","display":"Transformer","count":89},"x-feed-size-limit":100,"x-feed-sort":"enriched_at desc","x-feed-notice":"This feed contains at most 100 jobs (the most recently enriched). For the full corpus, use the paginated /stats/by-facet endpoint or /search.","x-generator":"yubhub-xml-generator","x-rights":"Free to redistribute with attribution: \"Data by YubHub (https://yubhub.co)\"","x-schema":"Each entry in `jobs` follows https://schema.org/JobPosting. YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6d7fadcc-6fa"},"title":"Data Scientist Computer Vision","description":"<p>At Bayer, we&#39;re seeking a talented Data Scientist with deep learning and machine learning expertise focused on image-based data to help shape the future of agriculture. In this role, you&#39;ll join a dynamic team that supports the development of Bayer Crop Science next-generation products by applying computer vision to automate critical processes across the Plant Biotechnology organisation.</p>\n<p>The primary responsibilities of this role are to:</p>\n<p>Solve real agricultural problems using deep learning and AI across image and other data modalities, translating complex models into tangible business and scientific impact.</p>\n<p>Design and implement end-to-end machine learning pipelines for computer vision use cases, including segmentation, classification, detection, and multi-task learning.</p>\n<p>Prototype, evaluate, and iterate on cutting-edge architectures such as CNNs, Vision Transformers, foundational and large-scale vision models, ensuring state-of-the-art performance.</p>\n<p>Optimize models for accuracy, robustness, and inference efficiency, including experimentation with hyperparameters, compression, and deployment-oriented optimisations.</p>\n<p>Independently build scalable data pipelines for training, validation, and evaluation, including data ingestion, augmentation strategies, and active learning loops.</p>\n<p>Collaborate cross-functionally with product, data, and software engineering teams to integrate models into production systems and deliver reliable, maintainable solutions.</p>\n<p>Contribute to MLOps practices, including model versioning, deployment, monitoring, and retraining workflows using modern tooling and cloud-based platforms.</p>\n<p>Build strong cross-functional relationships and actively engage with the broader Data Science Community to share best practices, align on standards, and co-create innovative solutions.</p>\n<p>Present clear, compelling, and validated stories about experiments, results, and recommendations to peers, senior management, and internal customers to drive strategic and operational decisions.</p>\n<p>We seek an incumbent who possesses the following:</p>\n<p>M.S. with 2+ years of experience or Ph.D. in Computer Science, Electrical Engineering, or a related field with a focus on machine learning or computer vision.</p>\n<p>Proficiency in Python and experience with deep learning frameworks such as PyTorch or TensorFlow.</p>\n<p>Hands-on experience with modern computer vision architectures including models such as ResNet, UNet, DeepLab, YOLO, SegFormer, SAM, and Vision Transformers.</p>\n<p>Strong background in handling large-scale datasets and creating custom datasets, for example using frameworks such as Hugging Face Datasets.</p>\n<p>Solid understanding of core machine learning concepts including loss functions, regularization, optimisation, and learning rate scheduling.</p>\n<p>Experience developing and deploying models using cloud-based ML platforms such as AWS SageMaker.</p>\n<p>Familiarity with Unix environments, including bash, file systems, and core utilities.</p>\n<p>Strong engineering practices including use of Git, Docker, CI/CD pipelines, modular codebase design, and unit testing.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_6d7fadcc-6fa","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Bayer","sameAs":"https://talent.bayer.com","logo":"https://logos.yubhub.co/talent.bayer.com.png"},"x-apply-url":"https://talent.bayer.com/careers/job/562949976908666","x-work-arrangement":"onsite","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$109,370.40 - $164,055.60","x-skills-required":["Python","PyTorch","TensorFlow","ResNet","UNet","DeepLab","YOLO","SegFormer","SAM","Vision Transformers","Hugging Face Datasets","AWS SageMaker","Git","Docker","CI/CD pipelines","modular codebase design","unit testing"],"x-skills-preferred":[],"datePosted":"2026-04-18T22:11:10.602Z","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Manufacturing","skills":"Python, PyTorch, TensorFlow, ResNet, UNet, DeepLab, YOLO, SegFormer, SAM, Vision Transformers, Hugging Face Datasets, AWS SageMaker, Git, Docker, CI/CD pipelines, modular codebase design, unit testing","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":109370.4,"maxValue":164055.6,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f28927b0-573"},"title":"Machine Learning Systems Research Engineer, Agent Post-training - Enterprise GenAI","description":"<p>At Scale, our mission is to accelerate the development of AI applications. We are working on an arsenal of proprietary research and resources that serve all of our enterprise clients. As an ML Sys Research Engineer, you&#39;ll work on building out the algorithms for our next-gen Agent RL training platform, support large scale training, and research and integrate state-of-the-art technologies to optimize our ML system.</p>\n<p>Your customer will be other MLREs and AAIs on the Enterprise AI team who are taking the training algorithms and applying them to client use-cases ranging from next-generation AI cybersecurity firewall LLMs to training foundation healthtech search models.</p>\n<p>If you are excited about shaping the future of the modern AI movement, we would love to hear from you!</p>\n<p>Key Responsibilities:</p>\n<ul>\n<li>Build, profile and optimize our training and inference framework.</li>\n<li>Post-train state of the art models, developed both internally and from the community, to define stable post-training recipes for our enterprise engagements.</li>\n<li>Collaborate with ML teams to accelerate their research and development, and enable them to develop the next generation of models and data curation.</li>\n<li>Create a next-gen agent training algorithm for multi-agent/multi-tool rollouts.</li>\n</ul>\n<p>Ideal Candidate:</p>\n<ul>\n<li>At least 1-3 years of LLM training in a production environment.</li>\n<li>Passionate about system optimization.</li>\n<li>Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.</li>\n<li>Ability to demonstrate know-how on how to operate the architecture of the modern GPU cluster.</li>\n<li>Experience with multi-node LLM training and inference.</li>\n<li>Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc.</li>\n<li>Strong written and verbal communication skills to operate in a cross functional team environment.</li>\n<li>PhD or Masters in Computer Science or a related field.</li>\n</ul>\n<p>Compensation:</p>\n<p>We offer competitive compensation packages, including base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.</p>\n<p>Benefits:</p>\n<ul>\n<li>Comprehensive health, dental and vision coverage.</li>\n<li>Retirement benefits.</li>\n<li>A learning and development stipend.</li>\n<li>Generous PTO.</li>\n<li>Commuter stipend.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_f28927b0-573","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://www.scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4625341005","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$189,600-$237,000 USD","x-skills-required":["LLM training","System optimization","Post-training methods","GPU cluster operation","Multi-node LLM training","Inference","CUDA","Pytorch","Transformers","Flash attention"],"x-skills-preferred":[],"datePosted":"2026-04-18T16:00:01.664Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"LLM training, System optimization, Post-training methods, GPU cluster operation, Multi-node LLM training, Inference, CUDA, Pytorch, Transformers, Flash attention","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":189600,"maxValue":237000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_465e2cfb-ddc"},"title":"Staff Machine Learning Research Scientist, LLM Evals","description":"<p>As a Staff Machine Learning Research Scientist on the LLM Evals team, you will lead the development of novel evaluation methodologies, metrics, and benchmarks to measure the capabilities and limitations of frontier LLMs.</p>\n<p>Your primary responsibilities will include:</p>\n<ul>\n<li>Driving research on the effectiveness and limitations of existing LLM evaluation techniques.</li>\n<li>Designing and developing novel evaluation benchmarks for large language models, covering areas such as instruction following, factuality, robustness, and fairness.</li>\n<li>Communicating, collaborating, and building relationships with clients and peer teams to facilitate cross-functional projects.</li>\n<li>Collaborating with internal teams and external partners to refine metrics and create standardized evaluation protocols.</li>\n<li>Implementing scalable and reproducible evaluation pipelines using modern ML frameworks.</li>\n<li>Publishing research findings in top-tier AI conferences and contributing to open-source benchmarking initiatives.</li>\n<li>Mentoring and guiding research scientists and engineers, providing technical leadership across cross-functional projects.</li>\n<li>Staying deeply engaged with the ML research community, tracking emerging work and contributing to the advancement of LLM evaluation science.</li>\n</ul>\n<p>The ideal candidate will have 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development.</p>\n<p>You will thrive in a high-energy, fast-paced startup environment and be ready to dedicate the time and effort needed to drive impactful results.</p>\n<p>Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_465e2cfb-ddc","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4628044005","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$264,800-$331,000 USD","x-skills-required":["large language model","NLP","Transformer modeling","evaluation methodologies","metrics","benchmarks","instruction following","factuality","robustness","fairness"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:59:31.100Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; Seattle, WA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"large language model, NLP, Transformer modeling, evaluation methodologies, metrics, benchmarks, instruction following, factuality, robustness, fairness","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":264800,"maxValue":331000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_539e2a23-ddf"},"title":"Tech Lead Manager- MLRE, ML Systems","description":"<p>You will lead the development of our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline.</p>\n<p>You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimising the platform to enable our next generation LLM training, inference and data curation.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Building, profiling and optimising our training and inference framework.</li>\n<li>Collaborating with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation.</li>\n<li>Researching and integrating state-of-the-art technologies to optimise our ML system.</li>\n</ul>\n<p>The ideal candidate will have:</p>\n<ul>\n<li>Passionate about system optimisation.</li>\n<li>Experience with multi-node LLM training and inference.</li>\n<li>Experience with developing large-scale distributed ML systems.</li>\n<li>Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.</li>\n<li>Strong software engineering skills, proficient in frameworks and tools such as CUDA, PyTorch, transformers, flash attention, etc.</li>\n</ul>\n<p>Nice to haves include demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.</p>\n<p>Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_539e2a23-ddf","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4618046005","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$264,800-$331,000 USD","x-skills-required":["system optimisation","multi-node LLM training and inference","large-scale distributed ML systems","post-training methods","software engineering skills","CUDA","PyTorch","transformers","flash attention"],"x-skills-preferred":["next generation use cases for large language models","instruction tuning","RLHF","tool use","reasoning","agents","multimodal"],"datePosted":"2026-04-18T15:59:21.558Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"system optimisation, multi-node LLM training and inference, large-scale distributed ML systems, post-training methods, software engineering skills, CUDA, PyTorch, transformers, flash attention, next generation use cases for large language models, instruction tuning, RLHF, tool use, reasoning, agents, multimodal","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":264800,"maxValue":331000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_60a7e1e6-b51"},"title":"Tech Lead/Manager, Machine Learning Research Scientist- LLM Evals","description":"<p>As the leading data and evaluation partner for frontier AI companies, we&#39;re dedicated to advancing the evaluation and benchmarking of large language models (LLMs). Our Research teams work with the industry&#39;s leading AI labs to provide high-quality data and accelerate progress in GenAI research.</p>\n<p>We&#39;re seeking a Tech Lead Manager to lead a talented team of research scientists and research engineers focused on developing and implementing novel evaluation methodologies, metrics, and benchmarks to assess the capabilities and limitations of our cutting-edge LLMs.</p>\n<p>Key responsibilities:</p>\n<ul>\n<li>Lead a team of highly effective research scientists and research engineers on LLM evals.</li>\n<li>Conduct research on the effectiveness and limitations of existing LLM evaluation techniques.</li>\n<li>Design and develop novel evaluation benchmarks for large language models, covering areas such as instruction following, factuality, robustness, and fairness.</li>\n<li>Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.</li>\n<li>Collaborate with internal teams and external partners to refine metrics and create standardized evaluation protocols.</li>\n<li>Implement scalable and reproducible evaluation pipelines using modern ML frameworks.</li>\n<li>Publish research findings in top-tier AI conferences and contribute to open-source benchmarking initiatives.</li>\n</ul>\n<p>Ideal candidate has 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development. Experience supporting and leading a team of research scientists and research engineers is also required.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_60a7e1e6-b51","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4304790005","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$264,800-$331,000 USD","x-skills-required":["large language model","NLP","Transformer modeling","research and engineering development","team leadership","cross-functional collaboration","evaluation methodologies","metrics and benchmarks","scalable and reproducible evaluation pipelines","modern ML frameworks"],"x-skills-preferred":["published research in top-tier AI conferences","open-source benchmarking initiatives","customer-facing role"],"datePosted":"2026-04-18T15:59:10.794Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; Seattle, WA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"large language model, NLP, Transformer modeling, research and engineering development, team leadership, cross-functional collaboration, evaluation methodologies, metrics and benchmarks, scalable and reproducible evaluation pipelines, modern ML frameworks, published research in top-tier AI conferences, open-source benchmarking initiatives, customer-facing role","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":264800,"maxValue":331000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_840bab06-7be"},"title":"ML Research Engineer, ML Systems","description":"<p>Job Description:</p>\n<p>Scale&#39;s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM&#39;s, as well as evaluation of data quality.</p>\n<p>At Scale, we&#39;re uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale&#39;s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Build, profile and optimize our training and inference framework</li>\n<li>Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation</li>\n<li>Research and integrate state-of-the-art technologies to optimize our ML system</li>\n</ul>\n<p>Ideal Candidate:</p>\n<ul>\n<li>Strong excitement about system optimization</li>\n<li>Experience with multi-node LLM training and inference</li>\n<li>Experience with developing large-scale distributed ML systems</li>\n<li>Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc.</li>\n<li>Strong written and verbal communication skills and the ability to operate in a cross functional team environment</li>\n</ul>\n<p>Nice to Have:</p>\n<ul>\n<li>Demonstrated expertise in post-training methods &amp;/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.</li>\n</ul>\n<p>Compensation Packages:</p>\n<p>Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You&#39;ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.</p>\n<p>Please note that our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_840bab06-7be","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4534631005","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$189,600-$237,000 USD","x-skills-required":["System Optimization","Multi-node LLM Training and Inference","Large-Scale Distributed ML Systems","CUDA","Pytorch","Transformers","Flash Attention"],"x-skills-preferred":["Post-Training Methods","Next Generation Use Cases for Large Language Models","Instruction Tuning","RLHF","Tool Use","Reasoning","Agents","Multimodal"],"datePosted":"2026-04-18T15:58:47.020Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; Seattle, WA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"System Optimization, Multi-node LLM Training and Inference, Large-Scale Distributed ML Systems, CUDA, Pytorch, Transformers, Flash Attention, Post-Training Methods, Next Generation Use Cases for Large Language Models, Instruction Tuning, RLHF, Tool Use, Reasoning, Agents, Multimodal","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":189600,"maxValue":237000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_467be5c4-940"},"title":"Machine Learning Engineer","description":"<p>We&#39;re looking for a Machine Learning Engineer to join our Ads Engineering team. As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including personalized recommendations, search, and ranking systems, intelligent advertising systems, and large-scale machine learning pipelines.</p>\n<p>Our team works on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. You&#39;ll work on complex, real-world ML problems at massive scale, and contribute to technical strategy, architecture, and long-term ML roadmap.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Design, build, and deploy production-grade machine learning models and systems at scale</li>\n<li>Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring</li>\n<li>Build scalable data and model pipelines with strong reliability, observability, and automated retraining</li>\n<li>Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems</li>\n<li>Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions</li>\n<li>Improve system performance across latency, throughput, and model quality metrics</li>\n<li>Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph &amp; transformers based, and LLM evaluation/alignment</li>\n</ul>\n<p>Basic Qualifications:</p>\n<ul>\n<li>3-5+ years of experience building, deploying, and operating machine learning systems in production</li>\n<li>Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals</li>\n<li>ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)</li>\n<li>Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)</li>\n<li>Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure</li>\n<li>Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions</li>\n<li>Experience improving measurable metrics through applied machine learning</li>\n</ul>\n<p>Preferred Qualifications:</p>\n<ul>\n<li>Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems</li>\n<li>Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)</li>\n<li>Experience working with real-time systems and low-latency production environments</li>\n<li>Background in feature engineering, model optimization, and production monitoring</li>\n<li>Experience with LLM/Gen AI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale</li>\n<li>Advanced degree in Computer Science, Machine Learning, or related quantitative field</li>\n</ul>\n<p>Potential Teams:</p>\n<ul>\n<li>Ads Measurement Modeling</li>\n<li>Ads Targeting and Retrieval</li>\n<li>Advertiser Optimization</li>\n<li>Ads Marketplace Quality</li>\n<li>Ads Creative Effectiveness</li>\n<li>Ads Foundational Representations</li>\n<li>Ads Content Understanding</li>\n<li>Ads Ranking</li>\n<li>Feed Relevance</li>\n<li>Search and Answers Relevance</li>\n<li>ML Understanding</li>\n<li>Notifications Relevance</li>\n</ul>\n<p>Benefits:</p>\n<ul>\n<li>Comprehensive Healthcare Benefits and Income Replacement Programs</li>\n<li>401k with Employer Match</li>\n<li>Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support</li>\n<li>Family Planning Support</li>\n<li>Gender-Affirming Care</li>\n<li>Mental Health &amp; Coaching Benefits</li>\n<li>Flexible Vacation &amp; Paid Volunteer Time Off</li>\n<li>Generous Paid Parental Leave</li>\n</ul>\n<p>Pay Transparency:</p>\n<p>This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave.</p>\n<p>To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.</p>\n<p>The base salary range for this position is: $185,800-$260,100 USD</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_467be5c4-940","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Reddit","sameAs":"https://www.redditinc.com","logo":"https://logos.yubhub.co/redditinc.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/reddit/jobs/7131932","x-work-arrangement":"remote","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$185,800-$260,100 USD","x-skills-required":["Python","Java","Go","PyTorch","TensorFlow","XGBoost","Random Forests","Regressions","Transformers","CNNs","GNNs","Spark","Kafka","Ray","Airflow","BigQuery","Redis"],"x-skills-preferred":["Recommender systems","Search/ranking systems","Advertising/auction systems","Large-scale representation learning","Multimodal embedding systems","Distributed systems","Large-scale data processing","Real-time systems","Low-latency production environments","Feature engineering","Model optimization","Production monitoring","LLM/Gen AI techniques"],"datePosted":"2026-04-18T15:57:49.850Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - United States"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Java, Go, PyTorch, TensorFlow, XGBoost, Random Forests, Regressions, Transformers, CNNs, GNNs, Spark, Kafka, Ray, Airflow, BigQuery, Redis, Recommender systems, Search/ranking systems, Advertising/auction systems, Large-scale representation learning, Multimodal embedding systems, Distributed systems, Large-scale data processing, Real-time systems, Low-latency production environments, Feature engineering, Model optimization, Production monitoring, LLM/Gen AI techniques","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":185800,"maxValue":260100,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_e998910e-d8f"},"title":"Senior Machine Learning Engineer","description":"<p>We&#39;re looking for a Senior Machine Learning Engineer to join our Ads Engineering team. As a Senior Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including personalized recommendations, search, and ranking systems. You&#39;ll work on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes.</p>\n<p>Your responsibilities will include:</p>\n<ul>\n<li>Designing, building, and deploying production-grade machine learning models and systems at scale</li>\n<li>Owning the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring</li>\n<li>Building scalable data and model pipelines with strong reliability, observability, and automated retraining</li>\n<li>Working with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems</li>\n<li>Partnering cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions</li>\n</ul>\n<p>You&#39;ll work on a wide range of high-impact problems across the Reddit ecosystem, including recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, and multimodal embedding systems.</p>\n<p>To be successful in this role, you&#39;ll need:</p>\n<ul>\n<li>3-5+ years of experience building, deploying, and operating machine learning systems in production</li>\n<li>Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals</li>\n<li>ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)</li>\n<li>Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)</li>\n<li>Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure</li>\n<li>Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions</li>\n</ul>\n<p>Preferred qualifications include experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems, familiarity with distributed systems and large-scale data processing, and experience working with real-time systems and low-latency production environments.</p>\n<p>At Reddit, we&#39;re committed to building a workforce representative of the diverse communities we serve. We&#39;re proud to be an equal opportunity employer and are committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_e998910e-d8f","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Reddit","sameAs":"https://www.redditinc.com","logo":"https://logos.yubhub.co/redditinc.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/reddit/jobs/6960833","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","Java","Go","PyTorch","TensorFlow","XGBoost","Random Forests","Regressions","Transformers","CNNs","GNNs"],"x-skills-preferred":["Recommender systems","Search/ranking systems","Advertising/auction systems","Large-scale representation learning","Multimodal embedding systems","Distributed systems","Large-scale data processing","Real-time systems","Low-latency production environments"],"datePosted":"2026-04-18T15:56:54.058Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - Ontario, Canada"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Java, Go, PyTorch, TensorFlow, XGBoost, Random Forests, Regressions, Transformers, CNNs, GNNs, Recommender systems, Search/ranking systems, Advertising/auction systems, Large-scale representation learning, Multimodal embedding systems, Distributed systems, Large-scale data processing, Real-time systems, Low-latency production environments"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_01794f13-11a"},"title":"TPU Kernel Engineer","description":"<p>As a TPU Kernel Engineer at Anthropic, you&#39;ll be responsible for identifying and addressing performance issues across many different ML systems, including research, training, and inference. A significant portion of this work will involve designing and optimizing kernels for the TPU. You will also provide feedback to researchers about how model changes impact performance.</p>\n<p>Strong candidates will have a track record of solving large-scale systems problems and low-level optimization. They should have significant experience optimizing ML systems for TPUs, GPUs, or other accelerators, and be results-oriented with a bias towards flexibility and impact.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Identify and address performance issues across multiple ML systems</li>\n<li>Design and optimize kernels for the TPU</li>\n<li>Provide feedback to researchers on model changes and their impact on performance</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>Bachelor&#39;s degree or equivalent combination of education, training, and/or experience</li>\n<li>Relevant field of study</li>\n<li>Years of experience required will correlate with the internal job level requirements for the position</li>\n</ul>\n<p>Benefits:</p>\n<ul>\n<li>Competitive compensation and benefits</li>\n<li>Optional equity donation matching</li>\n<li>Generous vacation and parental leave</li>\n<li>Flexible working hours</li>\n<li>Lovely office space in which to collaborate with colleagues</li>\n</ul>\n<p>Note: This job description is a rewritten version of the original ad, focusing on the key responsibilities, requirements, and benefits.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_01794f13-11a","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4720576008","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$280,000-$850,000 USD","x-skills-required":["ML systems optimization","TPU kernel design and optimization","Large-scale systems problem-solving","Low-level optimization","Results-oriented approach"],"x-skills-preferred":["High-performance computing","Machine learning framework internals","Language modeling with transformers","Accelerator architecture","Collective communication algorithms"],"datePosted":"2026-04-18T15:53:09.480Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"ML systems optimization, TPU kernel design and optimization, Large-scale systems problem-solving, Low-level optimization, Results-oriented approach, High-performance computing, Machine learning framework internals, Language modeling with transformers, Accelerator architecture, Collective communication algorithms","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":280000,"maxValue":850000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_dc17980d-461"},"title":"Research Engineer, Interpretability","description":"<p>JOB TITLE: Research Engineer, Interpretability \\n LOCATION: San Francisco, CA \\n DEPARTMENT: AI Research &amp; Engineering \\n \\n JOB DESCRIPTION: \\n \\n When you see what modern language models are capable of, do you wonder, &quot;How do these things work? How can we trust them?&quot; \\n \\n The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe. \\n \\n Think of us as doing &quot;neuroscience&quot; of neural networks using &quot;microscopes&quot; we build - or reverse-engineering neural networks like binary programs. \\n \\n More resources to learn about our work: \\n - Our research blog - covering advances including Monosemantic Features and Circuits \\n - An Introduction to Interpretability from our research lead, Chris Olah \\n - The Urgency of Interpretability from CEO Dario Amodei \\n - Engineering Challenges Scaling Interpretability - directly relevant to this role \\n - 60 Minutes segment - Around 8:07, see a demo of tooling our team built \\n - New Yorker article - what it&#39;s like to work on one of AI&#39;s hardest open problems \\n \\n Even if you haven&#39;t worked on interpretability before, the infrastructure expertise is similar to what&#39;s needed across the lifecycle of a production language model: \\n - Pretraining: Training dictionary learning models looks a lot like model pretraining - creating stable, performant training jobs for massively parameterized models across thousands of chips \\n - Inference: Interp runs a customized inference stack. Day-to-day analysis requires services that allow editing a model&#39;s internal activations mid-forward-pass - for example, adding a &quot;steering vector&quot; \\n - Performance: Like all LLM work, we push up against the limits of hardware and software. Rather than squeezing the last 0.1%, we are focused on finding bottlenecks, fixing them and moving ahead given rapidly evolving research and safety mission \\n \\n The science keeps scaling - and it&#39;s now applied directly in safety audits on frontier models, with real deadlines. As our research has matured, engineering and infrastructure have become a bottleneck. Your work will have a direct impact on one of the most important open problems in AI. \\n \\n RESPONSIBILITIES: \\n - Build and maintain the specialized inference and training infrastructure that powers interpretability research - including instrumented forward/backward passes, activation extraction, and steering vector application \\n - Resolve scaling and efficiency bottlenecks through profiling, optimization, and close collaboration with peer infrastructure teams \\n - Design tools, abstractions, and platforms that enable researchers to rapidly experiment without hitting engineering barriers \\n - Help bring interpretability research into production safety audits - with real deadlines and high reliability expectations \\n - Work across the stack - from model internals and accelerator-level optimization to user-facing research tooling \\n \\n YOU MAY BE A GOOD FIT IF YOU: \\n - Have 5-10+ years of experience building software \\n - Are highly proficient in at least one programming language (e.g., Python, Rust, Go, Java) and productive with Python \\n - Are extremely curious about unfamiliar domains; can quickly learn and put that knowledge to work, e.g. diving into new layers of the stack to find bottlenecks \\n - Have a strong ability to prioritize the most impactful work and are comfortable operating with ambiguity and questioning assumptions \\n - Prefer fast-moving collaborative projects to extensive solo efforts \\n - Are curious about interpretability research and its role in AI safety (though no research experience is required!) \\n - Care about the societal impacts and ethics of your work \\n - Are comfortable working closely with researchers, translating research needs into engineering solutions. \\n \\n STRONG CANDIDATES MAY ALSO HAVE EXPERIENCE WITH: \\n - Optimizing the performance of large-scale distributed systems \\n - Language modeling fundamentals with transformers \\n - High Performance LLM optimization: memory management, compute efficiency, parallelism strategies, inference throughput optimization \\n - Working hands-on in a mainstream ML stack - PyTorch/CUDA on GPUs or JAX/XLA on TPUs \\n - Collaborating closely with researchers and building tooling to support research teams; or directly performed research with complex engineering challenges \\n \\n REPRESENTATIVE PROJECTS: \\n - Building Garcon, a tool that allows researchers to easily instrument LLMs to extract internal activations \\n - Designing and optimizing a pipeline to efficiently collect petabytes of transformer activations and shuffle them \\n - Profiling and optimizing ML training jobs, including multi-GPU parallelism and memory optimization \\n - Building a steered inference system that applies targeted interventions to model internals at scale (conceptually similar to Golden Gate Claude but for safety research) \\n \\n ROLE SPECIFIC LOCATION POLICY: \\n - This role is based in the San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis. \\n \\n The annual compensation range for this role is listed below. \\n For sales roles, the range provided is the role&#39;s On Target Earnings (\\&quot;OTE\\&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. \\n Annual Salary:\\\\$315,000-\\\\$560,000 USD</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_dc17980d-461","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4980430008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$315,000-$560,000 USD","x-skills-required":["Python","Rust","Go","Java","PyTorch","CUDA","JAX","XLA","High Performance LLM optimization","memory management","compute efficiency","parallelism strategies","inference throughput optimization"],"x-skills-preferred":["large-scale distributed systems","language modeling fundamentals","transformers","collaborating closely with researchers","building tooling to support research teams"],"datePosted":"2026-04-18T15:53:01.682Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Rust, Go, Java, PyTorch, CUDA, JAX, XLA, High Performance LLM optimization, memory management, compute efficiency, parallelism strategies, inference throughput optimization, large-scale distributed systems, language modeling fundamentals, transformers, collaborating closely with researchers, building tooling to support research teams","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":315000,"maxValue":560000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6cd37537-ea6"},"title":"Research Engineer, Machine Learning","description":"<p>We&#39;re seeking a Research Engineer, Machine Learning to join our Frontier AI team. As a key member of our team, you will distill and fine-tune transformer architectures for deployment on edge devices or compute-denied environments. You will propose and prototype LLM-based Agentic systems to solve real-world problems, leveraging the latest state-of-the-art techniques in the field. You will develop and maintain mission-relevant benchmarks and work cross-functionally with different business lines across Anduril to help discover and scope new research problems.</p>\n<p>In this role, you will have the opportunity to work on cutting-edge projects, collaborate with a talented team of engineers and researchers, and contribute to the development of impactful technologies. You will also have access to a comprehensive benefits package, including healthcare benefits, income protection, generous time off, and professional development opportunities.</p>\n<p>The ideal candidate will have a BS in Computer Science, Machine Learning, Electrical Engineering, or a related field, and 5+ years of experience developing and benchmarking ML algorithms. You will have strong Python skills with experience in ML frameworks such as PyTorch, and be eligible to obtain and maintain an active U.S. Secret security clearance.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_6cd37537-ea6","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anduril","sameAs":"https://www.anduril.com/","logo":"https://logos.yubhub.co/anduril.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/andurilindustries/jobs/4999658007","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$220,000-$292,000 USD","x-skills-required":["BS in Computer Science, Machine Learning, Electrical Engineering, or related field","5+ years experience developing and benchmarking ML algorithms","Strong Python skills with experience in ML frameworks such as PyTorch","Eligible to obtain and maintain an active U.S. Secret security clearance"],"x-skills-preferred":["Experience fine-tuning transformer-based model","Experience deploying deep-learning based models to edge devices or air-gapped environments","Prior experience in defense tech or start-up"],"datePosted":"2026-04-18T15:51:17.571Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Seattle, Washington, United States"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"BS in Computer Science, Machine Learning, Electrical Engineering, or related field, 5+ years experience developing and benchmarking ML algorithms, Strong Python skills with experience in ML frameworks such as PyTorch, Eligible to obtain and maintain an active U.S. Secret security clearance, Experience fine-tuning transformer-based model, Experience deploying deep-learning based models to edge devices or air-gapped environments, Prior experience in defense tech or start-up","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":220000,"maxValue":292000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2bc6ae79-8ee"},"title":"Staff Technical Lead for Inference & ML Performance","description":"<p>We&#39;re looking for a Staff Technical Lead for Inference &amp; ML Performance to guide a team in building and optimizing state-of-the-art inference systems. This role is intense yet deeply impactful.</p>\n<p>You&#39;ll shape the future of fal&#39;s inference engine and ensure our generative models achieve best-in-class performance. Your work directly impacts our ability to rapidly deliver cutting-edge creative solutions to users, from individual creators to global brands.</p>\n<p>Day-to-day, you&#39;ll set technical direction, guide your team to build high-performance inference solutions, and personally contribute to critical inference performance enhancements and optimizations. You&#39;ll collaborate closely with research &amp; applied ML teams, influence model inference strategies and deployment techniques, and drive advanced performance optimizations.</p>\n<p>As a leader, you&#39;ll mentor and scale your team, coach and expand your team of performance-focused engineers, and help them innovate, solve complex performance challenges, and level up their skills.</p>\n<p>To succeed in this role, you&#39;ll need to be deeply experienced in ML performance optimization, understand the full ML performance stack, and know inference inside-out. You&#39;ll also need to thrive in cross-functional collaboration and have excellent leadership skills.</p>\n<p>If you&#39;re ready to lead the future of inference performance at a fast-paced, high-growth frontier, apply now!</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_2bc6ae79-8ee","directApply":true,"hiringOrganization":{"@type":"Organization","name":"fal","sameAs":"https://fal.com","logo":"https://logos.yubhub.co/fal.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/fal/jobs/4012780009","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["ML performance optimization","PyTorch","TensorRT","TransformerEngine","Triton","CUTLASS kernels","Quantization","Kernel authoring","Compilation","Model parallelism","Distributed serving","Profiling"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:50:42.839Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"ML performance optimization, PyTorch, TensorRT, TransformerEngine, Triton, CUTLASS kernels, Quantization, Kernel authoring, Compilation, Model parallelism, Distributed serving, Profiling"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f1501830-aab"},"title":"Research Engineer, Machine Learning","description":"<p>We&#39;re seeking a Research Engineer, Machine Learning to join our Frontier AI team. As a key member of our team, you will work on building edge-compatible, generative AI systems into our Lattice software platform. This will involve distilling and fine-tuning transformer architectures for deployment on edge devices or compute-denied environments, proposing and prototyping LLM-based Agentic systems, and developing and maintaining mission-relevant benchmarks.</p>\n<p>You will work closely with different business lines across Anduril to help discover and scope new research problems. To be successful in this role, you will need a strong background in machine learning, experience developing and benchmarking ML algorithms, and strong Python skills with experience in ML frameworks such as PyTorch.</p>\n<p>The salary range for this role is $220,000-$292,000 USD, and highly competitive equity grants are included in the majority of full-time offers. Additionally, Anduril offers top-tier benefits for full-time employees, including comprehensive medical, dental, and vision plans, income protection, generous time off, family planning and parenting support, mental health resources, professional development, commuter benefits, and relocation assistance.</p>\n<p>If you&#39;re interested in this opportunity, please reach out to the recruiter assigned to this role to learn more about the specific compensation and benefit details associated with this role.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_f1501830-aab","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anduril","sameAs":"https://www.anduril.com/","logo":"https://logos.yubhub.co/anduril.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/andurilindustries/jobs/4999656007","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$220,000-$292,000 USD","x-skills-required":["Machine Learning","Python","PyTorch","Transformer Architectures","LLM-based Agentic Systems","Benchmarking"],"x-skills-preferred":["Experience fine-tuning transformer-based models","Deploying deep-learning based models to edge devices or air-gapped environments","Prior experience in defence tech or start-up"],"datePosted":"2026-04-18T15:49:15.130Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Washington, District of Columbia, United States"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, Python, PyTorch, Transformer Architectures, LLM-based Agentic Systems, Benchmarking, Experience fine-tuning transformer-based models, Deploying deep-learning based models to edge devices or air-gapped environments, Prior experience in defence tech or start-up","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":220000,"maxValue":292000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_994cf43a-1cf"},"title":"Research Scientist, Generative Modelling for Materials and Chemistry","description":"<p>At Google DeepMind, we&#39;re committed to equal employment opportunity and value diversity of experience, knowledge, backgrounds, and perspectives.</p>\n<p>We&#39;re a multidisciplinary team building state-of-the-art generative models in chemistry &amp; materials to accelerate scientific breakthroughs.</p>\n<p>As a Research Scientist in our Science unit, you will be at the forefront of applying generative AI to the &quot;Grand Challenge&quot; of predicting the structure and properties of complex matter.</p>\n<p>Your work will bridge the gap between in silico modeling and real-world laboratory discovery, particularly in areas where traditional computational methods are bottlenecked by time and complexity.</p>\n<p>Key responsibilities:</p>\n<ul>\n<li>Design and train advanced AI models (transformers, generative models, etc.) to model the structure and properties of complex physical systems.</li>\n</ul>\n<ul>\n<li>Develop deep understanding of scientific domains that can be used to identify novel modelling approaches.</li>\n</ul>\n<ul>\n<li>Design and execute robust ML experiments that allow for the accumulation of small improvements, sharing results through clear verbal and written communication.</li>\n</ul>\n<ul>\n<li>Collaborate with other scientists and engineers to help shape the research roadmap.</li>\n</ul>\n<p>About You</p>\n<p>You are fascinated by the intersection of AI and natural science and determined to help solve grand challenges facing humanity.</p>\n<p>In order to set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience:</p>\n<ul>\n<li>PhD / equivalent experience in computer science, computational chemistry, materials science, physics with a focus on atomistic simulation or structural biology.</li>\n</ul>\n<ul>\n<li>Fluency in generative models and transformers</li>\n</ul>\n<ul>\n<li>Excellent collaboration and communication skills</li>\n</ul>\n<ul>\n<li>Experience with modern deep learning frameworks</li>\n</ul>\n<p>In addition, the following would be an advantage:</p>\n<ul>\n<li>Record of high-impact published work at the intersection of AI and natural science, particularly chemistry and materials science.</li>\n</ul>\n<ul>\n<li>Demonstrated experience in geometric deep learning.</li>\n</ul>\n<p>Applications close on Monday 20th April at 5pm BST</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_994cf43a-1cf","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Google DeepMind","sameAs":"https://deepmind.com/","logo":"https://logos.yubhub.co/deepmind.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/deepmind/jobs/7705247","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["PhD in computer science, computational chemistry, materials science, physics","Generative models and transformers","Collaboration and communication skills","Modern deep learning frameworks","Geometric deep learning"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:49:07.729Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"PhD in computer science, computational chemistry, materials science, physics, Generative models and transformers, Collaboration and communication skills, Modern deep learning frameworks, Geometric deep learning"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d4a6ec69-e81"},"title":"Staff Machine Learning Engineer, Dev Platform Data and Discovery","description":"<p>We&#39;re looking for a highly skilled Staff Machine Learning Engineer to join our Developer Platform team. As a Staff Machine Learning Engineer, you will own projects from ideation to production, working with a cross-functional team to solve hard problems and create engaging interactive experiences for Reddit communities.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Lead projects from concept, design, implementation, to rollout, ensuring the highest quality and performance.</li>\n<li>Identify opportunities to enhance ranking capabilities by diving deep into our platform and understanding the needs of our customers.</li>\n<li>Design and develop applied machine learning models for modeled personalization, game taxonomy, and more, from ideation to production deployment.</li>\n<li>Collaborate with data scientists, product managers, and backend software engineers.</li>\n<li>Mentor junior team members, share knowledge, and contribute to the technical growth of the team.</li>\n<li>Provide guidance on machine learning best practices and methodologies.</li>\n<li>Conduct A/B tests and experiments to iterate and fine-tune algorithms and models.</li>\n<li>Stay updated on state-of-the-art algorithmic techniques and recognize promising innovations, adapting them to Reddit&#39;s unique platform and community.</li>\n</ul>\n<p>Minimum Qualifications:</p>\n<ul>\n<li>7+ years of experience in a relevant industry or academic background, preferably in a quantitative/modeling or highly scalable computing environment.</li>\n<li>Prior experience with personalized feed ranking.</li>\n<li>Proven track record of delivering complex machine learning projects from conception to deployment, preferably in real-world applications.</li>\n<li>Ability to lead and mentor machine learning engineers or data scientists.</li>\n<li>Strong communication skills to collaborate effectively with cross-functional teams and stakeholders.</li>\n<li>Demonstrated ability to innovate and stay updated with the latest advancements in machine learning and AI.</li>\n</ul>\n<p>Preferred Qualifications:</p>\n<ul>\n<li>Experience of orchestrating complicated data pipelines and system engineering on large-scale datasets.</li>\n<li>Proficiency with programming languages and statistical analysis.</li>\n<li>Prior experience with Sequence Modeling, Reinforcement Learning, or Transformer Architecture.</li>\n<li>Experience in Bayesian methodology and experimentation.</li>\n</ul>\n<p>Benefits:</p>\n<ul>\n<li>Comprehensive Healthcare Benefits and Income Replacement Programs.</li>\n<li>401k with Employer Match.</li>\n<li>Family Planning Support.</li>\n<li>Gender-Affirming Care.</li>\n<li>Mental Health &amp; Coaching Benefits.</li>\n<li>Flexible Vacation &amp; Paid Volunteer Time Off.</li>\n<li>Generous Paid Parental Leave.</li>\n</ul>\n<p>Pay Transparency:</p>\n<p>This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission.</p>\n<p>To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies.</p>\n<p>Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.</p>\n<p>The base salary range for this position is $230,000-$322,000 USD.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_d4a6ec69-e81","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Reddit","sameAs":"https://www.redditinc.com","logo":"https://logos.yubhub.co/redditinc.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/reddit/jobs/7377109","x-work-arrangement":"remote","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$230,000-$322,000 USD","x-skills-required":["Machine Learning","Personalized Feed Ranking","Applied Machine Learning Models","Programming Languages","Statistical Analysis"],"x-skills-preferred":["Sequence Modeling","Reinforcement Learning","Transformer Architecture","Bayesian Methodology","Experimentation"],"datePosted":"2026-04-18T15:48:57.691Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - United States"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, Personalized Feed Ranking, Applied Machine Learning Models, Programming Languages, Statistical Analysis, Sequence Modeling, Reinforcement Learning, Transformer Architecture, Bayesian Methodology, Experimentation","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":230000,"maxValue":322000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_040a59f5-1d2"},"title":"Research Engineer, Pretraining","description":"<p>We are seeking a Research Engineer to join our Pretraining team. In this role, you will conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development. You will also independently lead small research projects while collaborating with team members on larger initiatives.</p>\n<p>Key responsibilities include designing, running, and analyzing scientific experiments to advance our understanding of large language models. Additionally, you will optimize and scale our training infrastructure to improve efficiency and reliability, and develop and improve dev tooling to enhance team productivity.</p>\n<p>As a Research Engineer, you will contribute to the entire stack, from low-level optimizations to high-level model design. You will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.</p>\n<p>The ideal candidate will have an advanced degree in Computer Science, Machine Learning, or a related field, and strong software engineering skills with a proven track record of building complex systems. You should be familiar with Python and experience with deep learning frameworks, particularly PyTorch. Additionally, you should have expertise in large-scale machine learning, particularly in the context of language models.</p>\n<p>You will thrive in this role if you have significant software engineering experience, are results-oriented with a bias towards flexibility and impact, willing to take on tasks outside your job description to support the team, enjoy pair programming and collaborative work, and are eager to learn more about machine learning research.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_040a59f5-1d2","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5119713008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"£260,000-£630,000 GBP","x-skills-required":["Python","PyTorch","Machine Learning","Deep Learning","Software Engineering","Computer Science"],"x-skills-preferred":["GPU","Kubernetes","OS Internals","Reinforcement Learning","Language Modeling","Transformer Architectures"],"datePosted":"2026-04-18T15:46:36.925Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, Machine Learning, Deep Learning, Software Engineering, Computer Science, GPU, Kubernetes, OS Internals, Reinforcement Learning, Language Modeling, Transformer Architectures","baseSalary":{"@type":"MonetaryAmount","currency":"GBP","value":{"@type":"QuantitativeValue","minValue":260000,"maxValue":630000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_97212bdf-dd1"},"title":"Research Engineer, Interpretability","description":"<p>Job Title: Research Engineer, Interpretability</p>\n<p>About the Role:</p>\n<p>When you see what modern language models are capable of, do you wonder, &quot;How do these things work? How can we trust them?&quot; The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe.</p>\n<p>Think of us as doing &quot;neuroscience&quot; of neural networks using &quot;microscopes&quot; we build - or reverse-engineering neural networks like binary programs.</p>\n<p>More resources to learn about our work:</p>\n<ul>\n<li>Our research blog - covering advances including Monosemantic Features and Circuits</li>\n</ul>\n<ul>\n<li>An Introduction to Interpretability from our research lead, Chris Olah</li>\n</ul>\n<ul>\n<li>The Urgency of Interpretability from CEO Dario Amodei</li>\n</ul>\n<ul>\n<li>Engineering Challenges Scaling Interpretability - directly relevant to this role</li>\n</ul>\n<ul>\n<li>60 Minutes segment - Around 8:07, see a demo of tooling our team built</li>\n</ul>\n<ul>\n<li>New Yorker article - what it&#39;s like to work on one of AI&#39;s hardest open problems</li>\n</ul>\n<p>Even if you haven&#39;t worked on interpretability before, the infrastructure expertise is similar to what&#39;s needed across the lifecycle of a production language model:</p>\n<ul>\n<li>Pretraining: Training dictionary learning models looks a lot like model pretraining - creating stable, performant training jobs for massively parameterized models across thousands of chips</li>\n</ul>\n<ul>\n<li>Inference: Interp runs a customized inference stack. Day-to-day analysis requires services that allow editing a model&#39;s internal activations mid-forward-pass - for example, adding a &quot;steering vector&quot;</li>\n</ul>\n<ul>\n<li>Performance: Like all LLM work, we push up against the limits of hardware and software. Rather than squeezing the last 0.1%, we are focused on finding bottlenecks, fixing them and moving ahead given rapidly evolving research and safety mission</li>\n</ul>\n<p>The science keeps scaling - and it&#39;s now applied directly in safety audits on frontier models, with real deadlines. As our research has matured, engineering and infrastructure have become a bottleneck. Your work will have a direct impact on one of the most important open problems in AI.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Build and maintain the specialized inference and training infrastructure that powers interpretability research - including instrumented forward/backward passes, activation extraction, and steering vector application</li>\n</ul>\n<ul>\n<li>Resolve scaling and efficiency bottlenecks through profiling, optimization, and close collaboration with peer infrastructure teams</li>\n</ul>\n<ul>\n<li>Design tools, abstractions, and platforms that enable researchers to rapidly experiment without hitting engineering barriers</li>\n</ul>\n<ul>\n<li>Help bring interpretability research into production safety audits - with real deadlines and high reliability expectations</li>\n</ul>\n<ul>\n<li>Work across the stack - from model internals and accelerator-level optimization to user-facing research tooling</li>\n</ul>\n<p>You may be a good fit if you:</p>\n<ul>\n<li>Have 5-10+ years of experience building software</li>\n</ul>\n<ul>\n<li>Are highly proficient in at least one programming language (e.g., Python, Rust, Go, Java) and productive with Python</li>\n</ul>\n<ul>\n<li>Are extremely curious about unfamiliar domains; can quickly learn and put that knowledge to work, e.g. diving into new layers of the stack to find bottlenecks</li>\n</ul>\n<ul>\n<li>Have a strong ability to prioritize the most impactful work and are comfortable operating with ambiguity and questioning assumptions</li>\n</ul>\n<ul>\n<li>Prefer fast-moving collaborative projects to extensive solo efforts</li>\n</ul>\n<ul>\n<li>Are curious about interpretability research and its role in AI safety (though no research experience is required!)</li>\n</ul>\n<ul>\n<li>Care about the societal impacts and ethics of your work</li>\n</ul>\n<ul>\n<li>Are comfortable working closely with researchers, translating research needs into engineering solutions.</li>\n</ul>\n<p>Strong candidates may also have experience with:</p>\n<ul>\n<li>Optimizing the performance of large-scale distributed systems</li>\n</ul>\n<ul>\n<li>Language modeling fundamentals with transformers</li>\n</ul>\n<ul>\n<li>High Performance LLM optimization: memory management, compute efficiency, parallelism strategies, inference throughput optimization</li>\n</ul>\n<ul>\n<li>Working hands-on in a mainstream ML stack - PyTorch/CUDA on GPUs or JAX/XLA on TPUs</li>\n</ul>\n<ul>\n<li>Collaborating closely with researchers and building tooling to support research teams; or directly performed research with complex engineering challenges</li>\n</ul>\n<p>Representative Projects:</p>\n<ul>\n<li>Building Garcon, a tool that allows researchers to easily instrument LLMs to extract internal activations</li>\n</ul>\n<ul>\n<li>Designing and optimizing a pipeline to efficiently collect petabytes of transformer activations and shuffle them</li>\n</ul>\n<ul>\n<li>Profiling and optimizing ML training jobs, including multi-GPU parallelism and memory optimization</li>\n</ul>\n<ul>\n<li>Building a steered inference system that applies targeted interventions to model internals at scale (conceptually similar to Golden Gate Claude but for safety research)</li>\n</ul>\n<p>Role Specific Location Policy:</p>\n<ul>\n<li>This role is based in the San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis.</li>\n</ul>\n<p>The annual compensation range for this role is listed below.</p>\n<p>For sales roles, the range provided is the role&#39;s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</p>\n<p>Annual Salary: $315,000-$560,000 USD</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_97212bdf-dd1","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4980430008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$315,000-$560,000 USD","x-skills-required":["Python","Rust","Go","Java","PyTorch","CUDA","JAX","XLA","Transformers","High Performance LLM optimization","Memory management","Compute efficiency","Parallelism strategies","Inference throughput optimization"],"x-skills-preferred":["Optimizing the performance of large-scale distributed systems","Language modeling fundamentals","Collaborating closely with researchers and building tooling to support research teams"],"datePosted":"2026-04-18T15:46:01.999Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Rust, Go, Java, PyTorch, CUDA, JAX, XLA, Transformers, High Performance LLM optimization, Memory management, Compute efficiency, Parallelism strategies, Inference throughput optimization, Optimizing the performance of large-scale distributed systems, Language modeling fundamentals, Collaborating closely with researchers and building tooling to support research teams","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":315000,"maxValue":560000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_fc38e24f-97e"},"title":"Senior Machine Learning Engineer","description":"<p>We&#39;re looking for a Senior Machine Learning Engineer to join our Ads Engineering team. As a key member of our team, you will design and build production ML systems that power core experiences across the platform, including personalized recommendations, search, and ranking systems, intelligent advertising systems, and large-scale machine learning pipelines.</p>\n<p>Our team is responsible for building systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. You will work on high-impact systems that improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems.</p>\n<p>As a Senior Machine Learning Engineer, you will:</p>\n<ul>\n<li>Design, build, and deploy production-grade machine learning models and systems at scale</li>\n<li>Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring</li>\n<li>Build scalable data and model pipelines with strong reliability, observability, and automated retraining</li>\n<li>Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems</li>\n<li>Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions</li>\n<li>Improve system performance across latency, throughput, and model quality metrics</li>\n<li>Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph &amp; transformers based, and LLM evaluation/alignment</li>\n</ul>\n<p>Basic Qualifications:</p>\n<ul>\n<li>3-5+ years of experience building, deploying, and operating machine learning systems in production</li>\n<li>Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals</li>\n<li>ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)</li>\n<li>Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)</li>\n<li>Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure</li>\n<li>Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions</li>\n<li>Experience improving measurable metrics through applied machine learning</li>\n</ul>\n<p>Preferred Qualifications:</p>\n<ul>\n<li>Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems</li>\n<li>Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)</li>\n<li>Experience working with real-time systems and low-latency production environments</li>\n<li>Background in feature engineering, model optimization, and production monitoring</li>\n<li>Experience with LLM/Gen AI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale</li>\n<li>Advanced degree in Computer Science, Machine Learning, or related quantitative field</li>\n</ul>\n<p>Potential Teams:</p>\n<ul>\n<li>Ads Measurement Modeling</li>\n<li>Ads Targeting and Retrieval</li>\n<li>Advertiser Optimization</li>\n<li>Ads Marketplace Quality</li>\n<li>Ads Creative Effectiveness</li>\n<li>Ads Foundational Representations</li>\n<li>Ads Content Understanding</li>\n<li>Ads Ranking</li>\n<li>Feed Relevance</li>\n<li>Search and Answers Relevance</li>\n<li>ML Understanding</li>\n<li>Notifications Relevance</li>\n</ul>\n<p>Benefits:</p>\n<ul>\n<li>Comprehensive Healthcare Benefits and Income Replacement Programs</li>\n<li>401k with Employer Match</li>\n<li>Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support</li>\n<li>Family Planning Support</li>\n<li>Gender-Affirming Care</li>\n<li>Mental Health &amp; Coaching Benefits</li>\n<li>Flexible Vacation &amp; Paid Volunteer Time Off</li>\n<li>Generous Paid Parental Leave</li>\n</ul>\n<p>Pay Transparency:</p>\n<p>This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/. To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is $216,700-$303,400 USD</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_fc38e24f-97e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Reddit","sameAs":"https://www.redditinc.com","logo":"https://logos.yubhub.co/redditinc.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/reddit/jobs/6960831","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$216,700-$303,400 USD","x-skills-required":["Python","Java","Go","PyTorch","TensorFlow","XGBoost","Random Forests","Regressions","Transformers","CNNs","GNNs","Spark","Kafka","Ray","Airflow","BigQuery","Redis"],"x-skills-preferred":["Recommender systems","Search/ranking systems","Advertising/auction systems","Large-scale representation learning","Multimodal embedding systems","Distributed systems","Large-scale data processing","Real-time systems","Low-latency production environments","Feature engineering","Model optimization","Production monitoring","LLM/Gen AI techniques","LLM evaluation","Alignment","Fine-tuning","Knowledge distillation","RAG/agentic systems"],"datePosted":"2026-04-18T15:45:58.533Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - United States"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Java, Go, PyTorch, TensorFlow, XGBoost, Random Forests, Regressions, Transformers, CNNs, GNNs, Spark, Kafka, Ray, Airflow, BigQuery, Redis, Recommender systems, Search/ranking systems, Advertising/auction systems, Large-scale representation learning, Multimodal embedding systems, Distributed systems, Large-scale data processing, Real-time systems, Low-latency production environments, Feature engineering, Model optimization, Production monitoring, LLM/Gen AI techniques, LLM evaluation, Alignment, Fine-tuning, Knowledge distillation, RAG/agentic systems","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":216700,"maxValue":303400,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_bd9625d9-99b"},"title":"ML Infrastructure Engineer, Safeguards","description":"<p>We are seeking a Machine Learning Infrastructure Engineer to join our Safeguards organization, where you&#39;ll build and scale the critical infrastructure that powers our AI safety systems.</p>\n<p>As part of the Safeguards team, you&#39;ll design and implement ML infrastructure that powers Claude safety. Your work will directly contribute to making AI systems more trustworthy and aligned with human values, ensuring our models operate safely as they become more capable.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Design and build scalable ML infrastructure to support real-time and batch classifier and safety evaluations across our model ecosystem</li>\n<li>Build monitoring and observability tools to track model performance, data quality, and system health for safety-critical applications</li>\n<li>Collaborate with research teams to productionize safety research, translating experimental safety techniques into robust, scalable systems</li>\n<li>Optimize inference latency and throughput for real-time safety evaluations while maintaining high reliability standards</li>\n<li>Implement automated testing, deployment, and rollback systems for ML models in production safety applications</li>\n<li>Partner with Safeguards, Security, and Alignment teams to understand requirements and deliver infrastructure that meets safety and production needs</li>\n<li>Contribute to the development of internal tools and frameworks that accelerate safety research and deployment</li>\n</ul>\n<p>You may be a good fit if you:</p>\n<ul>\n<li>Have 5+ years of experience building production ML infrastructure, ideally in safety-critical domains like fraud detection, content moderation, or risk assessment</li>\n<li>Are proficient in Python and have experience with ML frameworks like PyTorch, TensorFlow, or JAX</li>\n<li>Have hands-on experience with cloud platforms (AWS, GCP) and container orchestration (Kubernetes)</li>\n<li>Understand distributed systems principles and have built systems that handle high-throughput, low-latency workloads</li>\n<li>Have experience with data engineering tools and building robust data pipelines (e.g., Spark, Airflow, streaming systems)</li>\n<li>Are results-oriented, with a bias towards reliability and impact in safety-critical systems</li>\n<li>Enjoy collaborating with researchers and translating cutting-edge research into production systems</li>\n<li>Care deeply about AI safety and the societal impacts of your work</li>\n</ul>\n<p>Strong candidates may have experience with:</p>\n<ul>\n<li>Working with large language models and modern transformer architectures</li>\n<li>Implementing A/B testing frameworks and experimentation infrastructure for ML systems</li>\n<li>Developing monitoring and alerting systems for ML model performance and data drift</li>\n<li>Building automated labeling systems and human-in-the-loop workflows</li>\n<li>Experience in trust &amp; safety, fraud prevention, or content moderation domains</li>\n<li>Knowledge of privacy-preserving ML techniques and compliance requirements</li>\n<li>Contributing to open-source ML infrastructure projects</li>\n</ul>\n<p>We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_bd9625d9-99b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4778843008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$320,000-$405,000 USD","x-skills-required":["Python","PyTorch","TensorFlow","JAX","Cloud platforms (AWS, GCP)","Container orchestration (Kubernetes)","Distributed systems principles","Data engineering tools (Spark, Airflow, streaming systems)"],"x-skills-preferred":["Large language models and modern transformer architectures","A/B testing frameworks and experimentation infrastructure for ML systems","Monitoring and alerting systems for ML model performance and data drift","Automated labeling systems and human-in-the-loop workflows","Trust & safety, fraud prevention, or content moderation domains","Privacy-preserving ML techniques and compliance requirements","Open-source ML infrastructure projects"],"datePosted":"2026-04-18T15:44:06.907Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, TensorFlow, JAX, Cloud platforms (AWS, GCP), Container orchestration (Kubernetes), Distributed systems principles, Data engineering tools (Spark, Airflow, streaming systems), Large language models and modern transformer architectures, A/B testing frameworks and experimentation infrastructure for ML systems, Monitoring and alerting systems for ML model performance and data drift, Automated labeling systems and human-in-the-loop workflows, Trust & safety, fraud prevention, or content moderation domains, Privacy-preserving ML techniques and compliance requirements, Open-source ML infrastructure projects","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":320000,"maxValue":405000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f49203e0-6c6"},"title":"Research Engineer, Science of Scaling","description":"<p>We are seeking a Research Engineer/Scientist to join the Science of Scaling team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Conduct research into the science of converting compute into intelligence</li>\n<li>Independently lead small research projects while collaborating with team members on larger initiatives</li>\n<li>Design, run, and analyze scientific experiments to advance our understanding of large language models</li>\n<li>Optimize training infrastructure to improve efficiency and reliability</li>\n<li>Develop dev tooling to enhance team productivity</li>\n</ul>\n<p>You may be a good fit if you:</p>\n<ul>\n<li>Have significant software engineering experience and a proven track record of building complex systems</li>\n<li>Hold an advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field</li>\n<li>Are proficient in Python and experienced with deep learning frameworks</li>\n<li>Are results-oriented with a bias towards flexibility and impact</li>\n<li>Enjoy pair programming and collaborative work, and are willing to take on tasks outside your job description to support the team</li>\n<li>View research and engineering as two sides of the same coin, seeking to understand all aspects of the research program to maximize impact</li>\n<li>Care about the societal impacts of your work and have ambitious goals for AI safety and general progress</li>\n</ul>\n<p>Strong candidates may have:</p>\n<ul>\n<li>Experience with JAX</li>\n<li>Experience with reinforcement learning</li>\n<li>Experience working on high-performance, large-scale ML systems</li>\n<li>Familiarity with accelerators, Kubernetes, and OS internals</li>\n<li>Experience with language modeling using transformer architectures</li>\n<li>Background in large-scale ETL processes</li>\n<li>Experience with distributed training at scale (thousands of accelerators)</li>\n</ul>\n<p>Strong candidates need not have:</p>\n<ul>\n<li>Experience in all of the above areas , we value breadth of interest and willingness to learn over checking every box</li>\n<li>Prior work specifically on language models or transformers; strong engineering fundamentals and ML knowledge transfer well</li>\n<li>An advanced degree , exceptional engineers with strong research instincts are equally encouraged to apply</li>\n</ul>\n<p>The annual compensation range for this role is £260,000-£630,000 GBP.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_f49203e0-6c6","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5126127008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"£260,000-£630,000 GBP","x-skills-required":["Python","Deep learning frameworks","Software engineering","Machine learning","Advanced degree in Computer Science or related field"],"x-skills-preferred":["JAX","Reinforcement learning","High-performance, large-scale ML systems","Accelerators","Kubernetes","OS internals","Language modeling using transformer architectures","Large-scale ETL processes","Distributed training at scale"],"datePosted":"2026-04-18T15:42:40.887Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Deep learning frameworks, Software engineering, Machine learning, Advanced degree in Computer Science or related field, JAX, Reinforcement learning, High-performance, large-scale ML systems, Accelerators, Kubernetes, OS internals, Language modeling using transformer architectures, Large-scale ETL processes, Distributed training at scale","baseSalary":{"@type":"MonetaryAmount","currency":"GBP","value":{"@type":"QuantitativeValue","minValue":260000,"maxValue":630000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_279d67f2-5b5"},"title":"Research Engineer / Research Scientist, Tokens","description":"<p>We&#39;re looking for a Research Engineer / Research Scientist to join our team. As a Research Engineer, you&#39;ll touch all parts of our code and infrastructure, whether that&#39;s making the cluster more reliable for our big jobs, improving throughput and efficiency, running and designing scientific experiments, or improving our dev tooling.</p>\n<p>You&#39;ll be working on large-scale ML systems from the ground up, making safe, steerable, trustworthy systems. You&#39;ll be excited to write code when you understand the research context and more broadly why it&#39;s important.</p>\n<p>Strong candidates may also have experience with high performance, large-scale ML systems, GPUs, Kubernetes, Pytorch, or OS internals, language modeling with transformers, reinforcement learning, and large-scale ETL.</p>\n<p>Representative projects may include optimizing the throughput of a new attention mechanism, comparing the compute efficiency of two Transformer variants, making a Wikipedia dataset in a format models can easily consume, scaling a distributed training job to thousands of GPUs, writing a design doc for fault tolerance strategies, and creating an interactive visualization of attention between tokens in a language model.</p>\n<p>The annual compensation range for this role is $350,000-$500,000 USD.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_279d67f2-5b5","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4951814008","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$350,000-$500,000 USD","x-skills-required":["software engineering","machine learning","high performance computing","Kubernetes","Pytorch","OS internals","language modeling","reinforcement learning","large-scale ETL"],"x-skills-preferred":["GPU","transformers","distributed training"],"datePosted":"2026-04-18T15:42:28.391Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York City, NY; New York City, NY | Seattle, WA; San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"software engineering, machine learning, high performance computing, Kubernetes, Pytorch, OS internals, language modeling, reinforcement learning, large-scale ETL, GPU, transformers, distributed training","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":350000,"maxValue":500000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_e9e3cff7-d9b"},"title":"Performance Engineer","description":"<p>As a Performance Engineer at Anthropic, you will be responsible for identifying and solving novel systems problems that arise when running machine learning algorithms at scale. Your expertise will be crucial in developing systems that optimize the throughput and robustness of our largest distributed systems.</p>\n<p>You will work closely with our team of researchers, engineers, and policy experts to build beneficial AI systems. Your contributions will have a direct impact on the development of our AI technology and its applications.</p>\n<p>We are looking for a highly motivated and experienced engineer who is passionate about solving complex systems problems and has a strong background in software engineering or machine learning. If you are excited about the opportunity to work on cutting-edge AI technology and make a meaningful contribution to the field, we encourage you to apply.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Identify and solve novel systems problems that arise when running machine learning algorithms at scale</li>\n<li>Develop systems that optimize the throughput and robustness of our largest distributed systems</li>\n<li>Collaborate with our team of researchers, engineers, and policy experts to build beneficial AI systems</li>\n<li>Contribute to the development of our AI technology and its applications</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>Significant software engineering or machine learning experience, particularly at supercomputing scale</li>\n<li>Results-oriented, with a bias towards flexibility and impact</li>\n<li>Ability to pick up slack, even if it goes outside your job description</li>\n<li>Enjoy pair programming</li>\n<li>Want to learn more about machine learning research</li>\n<li>Care about the societal impacts of your work</li>\n</ul>\n<p>Preferred qualifications:</p>\n<ul>\n<li>Experience with high-performance, large-scale ML systems</li>\n<li>GPU/Accelerator programming</li>\n<li>ML framework internals</li>\n<li>OS internals</li>\n<li>Language modeling with transformers</li>\n</ul>\n<p>Benefits:</p>\n<ul>\n<li>Competitive compensation and benefits</li>\n<li>Optional equity donation matching</li>\n<li>Generous vacation and parental leave</li>\n<li>Flexible working hours</li>\n<li>Lovely office space in which to collaborate with colleagues</li>\n</ul>\n<p>Guidance on Candidates&#39; AI Usage: Learn about our policy for using AI in our application process</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_e9e3cff7-d9b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4020350008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$280,000-$850,000 USD","x-skills-required":["software engineering","machine learning","high-performance computing","GPU/Accelerator programming","ML framework internals","OS internals","language modeling with transformers"],"x-skills-preferred":["pair programming","results-oriented","flexibility and impact","ability to pick up slack","enjoy learning"],"datePosted":"2026-04-18T15:40:07.874Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"software engineering, machine learning, high-performance computing, GPU/Accelerator programming, ML framework internals, OS internals, language modeling with transformers, pair programming, results-oriented, flexibility and impact, ability to pick up slack, enjoy learning","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":280000,"maxValue":850000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_9cd2a442-db1"},"title":"Research Scientist, Generative Modelling for Materials and Chemistry","description":"<p>At Google DeepMind, we&#39;re committed to creating extraordinary impact by harnessing diversity of experience, knowledge, backgrounds, and perspectives.</p>\n<p>We&#39;re looking for a Research Scientist to join our Science unit, where you&#39;ll be at the forefront of applying generative AI to predict the structure and properties of complex matter.</p>\n<p>As a Research Scientist, you&#39;ll design and train advanced AI models to model the structure and properties of complex physical systems, develop a deep understanding of scientific domains, and collaborate with other scientists and engineers to shape the research roadmap.</p>\n<p>Key responsibilities include designing and executing robust ML experiments, accumulating small improvements, and sharing results through clear verbal and written communication.</p>\n<p>To succeed in this role, you&#39;ll need a PhD or equivalent experience in computer science, computational chemistry, materials science, physics, or a related field, with fluency in generative models and transformers.</p>\n<p>Experience with modern deep learning frameworks and a record of high-impact published work at the intersection of AI and natural science are also advantageous.</p>\n<p>Applications close on Monday 20th April at 5pm BST.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_9cd2a442-db1","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Google DeepMind","sameAs":"https://deepmind.com/","logo":"https://logos.yubhub.co/deepmind.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/deepmind/jobs/7705247","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Generative models","Transformers","Deep learning frameworks","Computer science","Computational chemistry","Materials science","Physics"],"x-skills-preferred":["Geometric deep learning","High-impact published work at the intersection of AI and natural science"],"datePosted":"2026-04-18T15:38:53.811Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Generative models, Transformers, Deep learning frameworks, Computer science, Computational chemistry, Materials science, Physics, Geometric deep learning, High-impact published work at the intersection of AI and natural science"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_1819a743-ca5"},"title":"Engineering Manager, GPU (ML Accelerator)","description":"<p>About the role:</p>\n<p>As an Engineering Manager on Anthropic&#39;s performance and scaling teams, you will be responsible for ensuring your team identifies and removes bottlenecks, builds robust and durable solutions, and maximizes the efficiency of our systems.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems</li>\n<li>Become familiar with the team&#39;s technical stack enough to make targeted contributions as an individual contributor</li>\n<li>Manage day-to-day execution of the team&#39;s work</li>\n<li>Prioritize the team&#39;s work and manage projects in a highly dynamic, fast-paced environment</li>\n<li>Coach and support your reports in understanding, and pursuing, their professional growth</li>\n<li>Maintain a deep understanding of the team&#39;s technical work and its implications for AI safety</li>\n</ul>\n<p>You may be a good fit if you:</p>\n<ul>\n<li>Have 1+ years of management experience in a technical environment, particularly performance or distributed systems</li>\n<li>Have a background in machine learning, AI, or a similar related technical field</li>\n<li>Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development</li>\n<li>Excel at building strong relationships with stakeholders at all levels</li>\n<li>Are a quick learner, capable of understanding and contributing to discussions on complex technical topics</li>\n<li>Have experience managing teams through periods of rapid growth and change</li>\n</ul>\n<p>Strong candidates may also have experience with:</p>\n<ul>\n<li>High-performance, large-scale ML systems</li>\n<li>GPU/Accelerator programming</li>\n<li>ML framework internals</li>\n<li>OS internals</li>\n<li>Language modeling with transformers</li>\n</ul>\n<p>The annual compensation range for this role is $500,000-$850,000 USD.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_1819a743-ca5","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4741104008","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$500,000-$850,000 USD","x-skills-required":["Machine Learning","AI","Performance or Distributed Systems","GPU/Accelerator Programming","ML Framework Internals","OS Internals","Language Modeling with Transformers"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:37:19.926Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, AI, Performance or Distributed Systems, GPU/Accelerator Programming, ML Framework Internals, OS Internals, Language Modeling with Transformers","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":500000,"maxValue":850000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d65b3d3f-a10"},"title":"Electrical Engineer (EIT)","description":"<p>As an Electrical Engineer in Training (EIT) at xAI, you&#39;ll support the design, evaluation, and upkeep of electrical systems powering our cutting-edge facilities.</p>\n<p>Working onsite with seasoned engineers and multidisciplinary teams, you&#39;ll tackle challenges to ensure BV power distribution and backup systems are reliable, safe, and scalable.</p>\n<p>Responsibilities include participating in design meetings, conducting feasibility studies, supporting the design and construction process, ensuring compliance with industry standards and safety regulations, and contributing to troubleshooting power issues.</p>\n<p>You&#39;ll also assist in managing maintenance schedules, analyzing and forecasting power needs, implementing strategies for energy efficiency and cost reduction, and promoting a safe working environment.</p>\n<p>As an EIT, you&#39;ll work closely with senior engineers and team members, seeking guidance and contributing to team efforts.</p>\n<p>This is a challenging role that requires strong technical skills, excellent communication skills, and a willingness to learn and adapt to new situations.</p>\n<p>If you&#39;re interested in project management and supporting large-scale data center projects, this could be the ideal opportunity for you.</p>\n<p>At xAI, we operate with a flat organisational structure, and all employees are expected to be hands-on and contribute directly to the company&#39;s mission.</p>\n<p>Leadership is given to those who show initiative and consistently deliver excellence.</p>\n<p>Work ethic and strong prioritisation skills are important, and all employees are expected to have strong communication skills.</p>\n<p>They should be able to concisely and accurately share knowledge with their teammates.</p>\n<p>Basic qualifications include a Bachelor&#39;s Degree in Electrical Engineering or a related field, Engineer in Training (EIT) certification, and 2-4 years of relevant experience in data center operations or electrical engineering.</p>\n<p>You should have basic knowledge of data center electrical systems, including transformers, switchgear, generators, and UPS systems.</p>\n<p>Proficiency with tools like AutoCAD, Revit, Bluebeam, and SKM is also required.</p>\n<p>Interest in project management and supporting large-scale data center projects is a plus.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_d65b3d3f-a10","directApply":true,"hiringOrganization":{"@type":"Organization","name":"xAI","sameAs":"https://www.xai.com/","logo":"https://logos.yubhub.co/xai.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/xai/jobs/4753835007","x-work-arrangement":"onsite","x-experience-level":"entry","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["AutoCAD","Revit","Bluebeam","SKM","data center electrical systems","transformers","switchgear","generators","UPS systems"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:35:27.002Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Memphis, TN"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AutoCAD, Revit, Bluebeam, SKM, data center electrical systems, transformers, switchgear, generators, UPS systems"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_ab80b377-8d1"},"title":"Electrical Engineer","description":"<p>As an Electrical Engineer at xAI, you&#39;ll lead the design, evaluation, and optimisation of the electrical systems powering our cutting-edge facilities.</p>\n<p>Collaborating onsite with multidisciplinary teams, you&#39;ll drive solutions to ensure our power distribution and backup systems are reliable, safe, and scalable.</p>\n<p>Dive into complex technical challenges, mentor junior staff, and deliver innovations that support mission-critical operations, advancing xAI&#39;s goal of accelerating human scientific discovery through AI.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Lead design meetings for electrical systems in new data center builds and expansions, providing expert input from an electrical engineering perspective.</li>\n</ul>\n<ul>\n<li>Conduct feasibility studies and develop detailed specifications for system components.</li>\n</ul>\n<ul>\n<li>Oversee the design and construction process, including permitting, collaborating with licensed engineers and stakeholders.</li>\n</ul>\n<ul>\n<li>Manage the installation of power distribution units (PDUs), UPS systems, cooling units, and other critical infrastructure.</li>\n</ul>\n<ul>\n<li>Ensure full compliance with industry standards (e.g., Uptime Institute Tier Standards), safety regulations, and company policies.</li>\n</ul>\n<ul>\n<li>Develop and manage maintenance schedules to ensure electrical systems operate at peak efficiency.</li>\n</ul>\n<ul>\n<li>Lead troubleshooting of power issues, minimising downtime and enhancing system reliability.</li>\n</ul>\n<ul>\n<li>Perform in-depth analysis and forecasting of power needs based on current and projected IT loads.</li>\n</ul>\n<ul>\n<li>Implement strategies for energy efficiency, cost reduction, and sustainability.</li>\n</ul>\n<ul>\n<li>Collaborate with senior engineers and cross-functional teams, providing guidance and driving collective efforts.</li>\n</ul>\n<ul>\n<li>Champion a culture of continuous improvement, innovation, and knowledge sharing within the team.</li>\n</ul>\n<ul>\n<li>Lead project management for infrastructure initiatives, from conception through commissioning.</li>\n</ul>\n<ul>\n<li>Coordinate with external vendors, contractors, and internal departments to deliver projects on time and within budget.</li>\n</ul>\n<ul>\n<li>Verify all work complies with local, state, and federal regulations concerning electrical systems.</li>\n</ul>\n<ul>\n<li>Foster a safe working environment by enforcing and promoting safety protocols.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_ab80b377-8d1","directApply":true,"hiringOrganization":{"@type":"Organization","name":"xAI","sameAs":"https://www.xai.com/","logo":"https://logos.yubhub.co/xai.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/xai/jobs/4977264007","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["data center electrical systems","transformers","switchgear","generators","UPS systems","AutoCAD","Revit","Bluebeam","SKM","power system analysis software","project management"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:35:17.865Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Memphis, TN"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"data center electrical systems, transformers, switchgear, generators, UPS systems, AutoCAD, Revit, Bluebeam, SKM, power system analysis software, project management"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_9f6fed50-cc0"},"title":"Applied AI, AI Engineer","description":"<p>About the Job</p>\n<p>We are seeking an Applied AI, AI Engineer to join our customer-facing technical organization. As a member of our team, you will work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact.</p>\n<p>Your primary responsibility will be to identify high-value internal use cases across engineering, legal, HR, sales, and operations, and build or vibe code end-to-end LLM applications. You will own the full lifecycle of these applications, from prototype to production, maintenance, and iteration.</p>\n<p>In addition to your technical skills, you will also be responsible for documenting learnings and sharing insights with product and research teams, and converting successful internal tools into customer demos or case studies where appropriate.</p>\n<p>How We Work in Applied AI</p>\n<p>We care about people and outputs. What matters is what you ship, not the time you spend on it. Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. Always ask why. The best solutions come from deep understanding, not from copying what worked before. We say what we mean. Feedback is direct, timely, and given because we care. No politics. Low ego, high standards. We embrace an unstructured environment and find joy in it.</p>\n<p>About You</p>\n<p>You are fluent in English and have 3+ years of experience building production software, with meaningful experience deploying LLM applications. You have a bias toward shipping, preferring a working prototype over a perfect specification. You possess strong technical coding skills in Python and front-end skills with React Frameworks. You are comfortable working autonomously across teams with different needs and constraints, and have strong communication skills to bridge non-technical teams and AI capabilities.</p>\n<p>Ideally, you have contributions to open-source evaluation frameworks or published research on LLM evaluation, experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, or Technical Product Manager, and experience with ML frameworks (PyTorch, HuggingFace Transformers).</p>\n<p>Benefits</p>\n<p>PTO: The CDI contract will be a &#39;Forfait 218 jours&#39;, corresponding to 25 days of holidays and on average 8 to 10 days of RTT days, and complete autonomy on working hours.</p>\n<p>Health: Full health insurance coverage for you and your family.</p>\n<p>Transportation: We offer a €600 annual mobility allowance, covering 50% of your public transportation costs and including the Sustainable Mobility Allowance (FMD), encouraging eco-friendly travel options such as cycling or carpooling.</p>\n<p>Food: Swile meal vouchers with 10,83€ per worked day, including 60% offered by the company.</p>\n<p>Sport: Gymlib - sponsorship by Mistral of a significant part of the monthly fee (depending on the program you chose).</p>\n<p>Parental policy: 4 additional weeks for parents on top of what is offered by the French state.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_9f6fed50-cc0","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral AI","sameAs":"https://mistral.ai","logo":"https://logos.yubhub.co/mistral.ai.png"},"x-apply-url":"https://jobs.lever.co/mistral/3d9a6ece-1f8c-4e0b-a275-fde6300ed1f8","x-work-arrangement":"onsite","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","React Frameworks","LLM applications","PyTorch","HuggingFace Transformers"],"x-skills-preferred":["Open-source evaluation frameworks","Published research on LLM evaluation","Customer Engineer","Forward Deployed Engineer","Sales Engineer","Solutions Architect","Technical Product Manager"],"datePosted":"2026-04-17T12:46:55.240Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, React Frameworks, LLM applications, PyTorch, HuggingFace Transformers, Open-source evaluation frameworks, Published research on LLM evaluation, Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, Technical Product Manager"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c7da135a-ebe"},"title":"Applied AI, Evaluation Engineer","description":"<p>About the Job</p>\n<p>The Applied AI team is Mistral&#39;s customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact.</p>\n<p>As a first Evaluation Engineer, you&#39;ll design the methodology, build the infrastructure, and define what &#39;ready for production&#39; means across verticals and use cases. You will design and implement evaluation systems that help our customers understand model performance across their specific use cases, build robust evaluation infrastructure, and work closely with both research and customer-facing teams.</p>\n<p>Research builds evals for frontier capabilities but customers don&#39;t care about MMLU scores. We need in Applied AI evals and frameworks for customer reality domain-specific, risk-aware, production-grade. The kind that tell you whether your medical summarization model will hallucinate drug interactions, or whether your legal assistant will invent case citations.</p>\n<p>This role sits at the intersection of research, engineering, and solutions, you will play a critical cross role in measuring, understanding, and improving the capabilities of our models for our enterprise customers.</p>\n<p>Responsibilities</p>\n<ul>\n<li><p>Design and implement comprehensive evaluation frameworks to measure LLM capabilities across diverse customer use cases, including text generation, reasoning, code, and domain-specific applications</p>\n</li>\n<li><p>Build scalable evaluation infrastructure and pipelines that enable rapid, reproducible assessment of model performance</p>\n</li>\n<li><p>Develop novel evaluation methodologies to assess emerging capabilities or verticalized use cases (cybersecurity, finance, healthcare, etc.) and enable the Solutions (Deployment Strategist and Applied AI) on these topics</p>\n</li>\n<li><p>Create custom evaluation suites tailored to enterprise customers&#39; specific needs, working closely with them to understand their requirements and success criteria</p>\n</li>\n<li><p>Collaborate with research teams to translate evaluation insights into model improvements and training decisions</p>\n</li>\n<li><p>Partner with product teams to continuously improve our evaluation tooling based on customer feedback</p>\n</li>\n</ul>\n<p>How We Work in Applied AI</p>\n<ul>\n<li><p>We care about people and outputs</p>\n</li>\n<li><p>What matters is what you ship, not the time you spend on it</p>\n</li>\n<li><p>Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to</p>\n</li>\n<li><p>The best idea wins, whether it comes from a principal engineer or someone in their first week</p>\n</li>\n<li><p>Always ask why. The best solutions come from deep understanding, not from copying what worked before</p>\n</li>\n<li><p>We say what we mean. Feedback is direct, timely, and given because we care</p>\n</li>\n<li><p>No politics. Low ego, high standards</p>\n</li>\n<li><p>We embrace an unstructured environment and find joy in it</p>\n</li>\n</ul>\n<p>About You</p>\n<ul>\n<li><p>You are fluent in English</p>\n</li>\n<li><p>3+ years of experience in ML evaluation, benchmarking for LLM or agentic systems</p>\n</li>\n<li><p>You have proven experience in AI or machine learning product implementation with APIs, back-end</p>\n</li>\n<li><p>You have deep understanding of concepts and algorithms underlying machine learning and LLMs</p>\n</li>\n<li><p>You have strong technical coding skills in Python</p>\n</li>\n<li><p>You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences</p>\n</li>\n</ul>\n<p>Ideally You Have:</p>\n<ul>\n<li><p>Contributions to open-source evaluation frameworks (e.g., LM Eval Harness, OpenAI Evals) or published research on LLM evaluation</p>\n</li>\n<li><p>Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager</p>\n</li>\n<li><p>Experience with ML frameworks (PyTorch, HuggingFace Transformers)</p>\n</li>\n</ul>\n<p>Benefits</p>\n<ul>\n<li><p>PTO: The CDI contract will be a &#39;Forfait 218 jours&#39;, corresponding to 25 days of holidays and on average 8 to 10 days of RTT days, and complete autonomy on working hours</p>\n</li>\n<li><p>Health: Full health insurance coverage for you and your family</p>\n</li>\n<li><p>Transportation: We offer a €600 annual mobility allowance. This package covers 50% of your public transportation costs and includes the Sustainable Mobility Allowance (FMD), encouraging eco-friendly travel options such as cycling or carpooling</p>\n</li>\n<li><p>Food: Swile meal vouchers with 10,83€ per worked day, incl 60% offered by company</p>\n</li>\n<li><p>Sport: Gymlib - sponsorship by Mistral of a significant part of the monthly fee (depending on the program you chose)</p>\n</li>\n<li><p>Parental policy: 4 additional weeks for parents on top of what is offered by the French state</p>\n</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_c7da135a-ebe","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral AI","sameAs":"https://mistral.ai","logo":"https://logos.yubhub.co/mistral.ai.png"},"x-apply-url":"https://jobs.lever.co/mistral/e0db3860-0a80-47a8-958a-f8e62f3bb59c","x-work-arrangement":"onsite","x-experience-level":"entry","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["ML evaluation","benchmarking for LLM or agentic systems","AI or machine learning product implementation with APIs, back-end","Python","evaluation frameworks","open-source evaluation frameworks","PyTorch","HuggingFace Transformers"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:46:40.159Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"ML evaluation, benchmarking for LLM or agentic systems, AI or machine learning product implementation with APIs, back-end, Python, evaluation frameworks, open-source evaluation frameworks, PyTorch, HuggingFace Transformers"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_eb286b66-47b"},"title":"AI Scientist","description":"<p>About this role</p>\n<p>We&#39;re looking for an AI Scientist to join our research team in Zurich. As an AI Scientist, you will research and develop novel methods to push the frontier of large language models. You will work across use cases (e.g., reasoning, code, agents) and modalities (e.g., text, image, and speech). You will build tooling and infrastructure to allow training, evaluation, and analysis of AI models at scale. You will also work cross-functionally with other scientists, engineers, and product teams to ship AI systems that have a real-world impact.</p>\n<p>About you</p>\n<ul>\n<li>You are a highly proficient software engineer in at least one programming language (Python or other, e.g., Rust, Go, Java).</li>\n<li>You have hands-on experience with AI frameworks (e.g., PyTorch, JAX) or distributed systems (e.g., Ray, Kubernetes).</li>\n<li>You have high engineering competence. This means being able to design complex software and make it usable in production.</li>\n<li>You are a self-starter, autonomous, and a team player.</li>\n</ul>\n<p>Now, it would be ideal if</p>\n<ul>\n<li>You have hands-on experience with training large transformer models in a distributed fashion.</li>\n<li>You are able to navigate the full MLOps stack, for instance, fine-tuning, evaluation, and deployment.</li>\n<li>You have a strong publication record in a relevant scientific domain.</li>\n</ul>\n<p>Benefits</p>\n<ul>\n<li>Competitive cash salary and equity</li>\n<li>Food: Monthly meal allowance</li>\n<li>Sport: Monthly contribution to a Gympass subscription</li>\n<li>Private pension plan</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_eb286b66-47b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral AI","sameAs":"https://mistral.ai","logo":"https://logos.yubhub.co/mistral.ai.png"},"x-apply-url":"https://jobs.lever.co/mistral/bedfc2aa-f1b6-4136-bd17-b3abe4c06120","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","PyTorch","JAX","Rust","Go","Java","Ray","Kubernetes"],"x-skills-preferred":["Training large transformer models in a distributed fashion","Navigating the full MLOps stack","Strong publication record in a relevant scientific domain"],"datePosted":"2026-04-17T12:46:40.057Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Zurich"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, JAX, Rust, Go, Java, Ray, Kubernetes, Training large transformer models in a distributed fashion, Navigating the full MLOps stack, Strong publication record in a relevant scientific domain"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6ea4460a-445"},"title":"AI Scientist","description":"<p>About Mistral</p>\n<p>At Mistral, we are on a mission to democratize AI, producing frontier intelligence for everyone. We develop models for the enterprise and for consumers, focusing on delivering systems which can really change the way in which businesses operate and which can integrate into our daily lives.</p>\n<p>What will you do?</p>\n<ul>\n<li>Research and develop novel methods to push the frontier of large language models</li>\n<li>Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech)</li>\n<li>Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale</li>\n<li>Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact</li>\n</ul>\n<p>About you</p>\n<ul>\n<li>You are a highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java)</li>\n<li>You have hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes)</li>\n<li>You have high engineering competence. This means being able to design complex software and make it usable in production</li>\n<li>You are a self-starter, autonomous and a team player</li>\n</ul>\n<p>Now, it would be ideal if</p>\n<ul>\n<li>You have hands-on experience with training large transformer models in a distributed fashion</li>\n<li>You are able to navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment</li>\n<li>You have a strong publication record in a relevant scientific domain</li>\n</ul>\n<p>Benefits</p>\n<p>France</p>\n<ul>\n<li>Competitive cash salary and equity</li>\n<li>Food: Daily lunch vouchers</li>\n<li>Sport: Monthly contribution to a Gympass subscription</li>\n<li>Transportation: Monthly contribution to a mobility pass</li>\n<li>Health: Full health insurance for you and your family</li>\n<li>Parental: Generous parental leave policy</li>\n</ul>\n<p>UK</p>\n<ul>\n<li>Competitive cash salary and equity</li>\n<li>Insurance</li>\n<li>Transportation: Reimburse office parking charges, or 90GBP/month for public transport</li>\n<li>Sport: 90GBP/month reimbursement for gym membership</li>\n<li>Meal voucher: £200 monthly allowance for its meals</li>\n<li>Pension plan: SmartPension (percentages are 5% Employee &amp; 3% Employer)</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_6ea4460a-445","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral","sameAs":"https://www.mistral.ai/","logo":"https://logos.yubhub.co/mistral.ai.png"},"x-apply-url":"https://jobs.lever.co/mistral/675b7f06-a76b-4144-af0c-4dd3282ef489","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","PyTorch","JAX","Rust","Go","Java","Ray","Kubernetes"],"x-skills-preferred":["Training large transformer models in a distributed fashion","Navigating the full MLOps stack","Strong publication record in a relevant scientific domain"],"datePosted":"2026-04-17T12:46:10.643Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, JAX, Rust, Go, Java, Ray, Kubernetes, Training large transformer models in a distributed fashion, Navigating the full MLOps stack, Strong publication record in a relevant scientific domain"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_8c72b249-b04"},"title":"AI Scientist","description":"<p>About the Role</p>\n<p>We are seeking an AI Scientist to join our research team in Warsaw. As an AI Scientist, you will research and develop novel methods to push the frontier of large language models, work across use cases and modalities, and build tooling and infrastructure to allow training, evaluation, and analysis of AI models at scale.</p>\n<p>Responsibilities</p>\n<p>• Research and develop novel methods to push the frontier of large language models\n• Work across use cases (e.g., reasoning, code, agents) and modalities (e.g., text, image, and speech)\n• Build tooling and infrastructure to allow training, evaluation, and analysis of AI models at scale\n• Work cross-functionally with other scientists, engineers, and product teams to ship AI systems that have a real-world impact</p>\n<p>About You</p>\n<p>• You are a highly proficient software engineer in at least one programming language (Python or other, e.g., Rust, Go, Java)\n• You have hands-on experience with AI frameworks (e.g., PyTorch, JAX) or distributed systems (e.g., Ray, Kubernetes)\n• You have high engineering competence. This means being able to design complex software and make it usable in production\n• You are a self-starter, autonomous, and a team player</p>\n<p>Benefits</p>\n<p>• Competitive cash salary and equity\n• Food: Monthly meal allowance\n• Sport: Monthly contribution to a Gympass subscription\n• Private pension plan</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_8c72b249-b04","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral AI","sameAs":"https://mistral.ai","logo":"https://logos.yubhub.co/mistral.ai.png"},"x-apply-url":"https://jobs.lever.co/mistral/4e498cbf-151e-483a-b3f7-76ff64a22041","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","PyTorch","JAX","Rust","Go","Java","Ray","Kubernetes"],"x-skills-preferred":["Training large transformer models in a distributed fashion","Navigating the full MLOps stack, for instance, fine-tuning, evaluation, and deployment","Strong publication record in a relevant scientific domain"],"datePosted":"2026-04-17T12:46:09.065Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Warsaw"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, JAX, Rust, Go, Java, Ray, Kubernetes, Training large transformer models in a distributed fashion, Navigating the full MLOps stack, for instance, fine-tuning, evaluation, and deployment, Strong publication record in a relevant scientific domain"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_75be3667-194"},"title":"AI Scientist - Audio","description":"<p>About Mistral</p>\n<p>At Mistral, we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world.</p>\n<p>We develop models for the enterprise and for consumers, focusing on delivering systems which can really change the way in which businesses operate and which can integrate into our daily lives. All while releasing frontier models open-source, for everyone to try and benefit.</p>\n<p>What will you do?</p>\n<ul>\n<li>Research and develop novel methods to push the frontier of large language models</li>\n<li>Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech)</li>\n<li>Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale</li>\n<li>Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact</li>\n</ul>\n<p>About you</p>\n<ul>\n<li>An expert in speech input/output methodologies (specific to audio)</li>\n<li>Highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java)</li>\n<li>Hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes)</li>\n<li>High engineering competence. This means being able to design complex software and make it usable in production</li>\n<li>Self-starter, autonomous and a team player</li>\n</ul>\n<p>Now, it would be ideal if</p>\n<ul>\n<li>You have experience working with large-scale speech-language models</li>\n<li>You have hands-on experience with training large transformer models in a distributed fashion</li>\n<li>You can navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment</li>\n<li>You have a strong publication record in a relevant scientific domain</li>\n</ul>\n<p>Benefits</p>\n<p>France</p>\n<ul>\n<li>Competitive cash salary and equity</li>\n<li>Food: Daily lunch vouchers</li>\n<li>Sport: Monthly contribution to a Gympass subscription</li>\n<li>Transportation: Monthly contribution to a mobility pass</li>\n<li>Health: Full health insurance for you and your family</li>\n<li>Parental: Generous parental leave policy</li>\n</ul>\n<p>UK</p>\n<ul>\n<li>Competitive cash salary and equity</li>\n<li>Insurance</li>\n<li>Transportation: Reimburse office parking charges, or 90GBP/month for public transport</li>\n<li>Sport: 90GBP/month reimbursement for gym membership</li>\n<li>Meal voucher: £200 monthly allowance for its meals</li>\n<li>Pension plan: SmartPension (percentages are 5% Employee &amp; 3% Employer)</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_75be3667-194","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral","sameAs":"https://www.mistral.ai/","logo":"https://logos.yubhub.co/mistral.ai.png"},"x-apply-url":"https://jobs.lever.co/mistral/94173e13-3050-4044-862a-e8dfc2deda5e","x-work-arrangement":"hybrid","x-experience-level":null,"x-job-type":"full-time","x-salary-range":null,"x-skills-required":["speech input/output methodologies","Python","PyTorch","JAX","Rust","Go","Java","distributed systems","Ray","Kubernetes"],"x-skills-preferred":["large-scale speech-language models","training large transformer models in a distributed fashion","MLOps stack","fine-tuning","evaluation","deployment"],"datePosted":"2026-04-17T12:46:02.015Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"speech input/output methodologies, Python, PyTorch, JAX, Rust, Go, Java, distributed systems, Ray, Kubernetes, large-scale speech-language models, training large transformer models in a distributed fashion, MLOps stack, fine-tuning, evaluation, deployment"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_fe6b2de2-36b"},"title":"AI Scientist","description":"<p>About Mistral</p>\n<p>At Mistral, we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world.</p>\n<p>We develop models for the enterprise and for consumers, focusing on delivering systems which can really change the way in which businesses operate and which can integrate into our daily lives. All while releasing frontier models open-source, for everyone to try and benefit.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Research and develop novel methods to push the frontier of large language models</li>\n<li>Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech)</li>\n<li>Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale</li>\n<li>Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact</li>\n</ul>\n<p><strong>About You</strong></p>\n<ul>\n<li>You are a highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java)</li>\n<li>You have hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes)</li>\n<li>You have high engineering competence. This means being able to design complex software and make it usable in production</li>\n<li>You are a self-starter, autonomous and a team player</li>\n</ul>\n<p>Now, it would be ideal if</p>\n<ul>\n<li>You have hands-on experience with training large transformer models in a distributed fashion</li>\n<li>You are able to navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment</li>\n<li>You have a strong publication record in a relevant scientific domain</li>\n<li>Audio/Speech experience - audio input/out, NLP</li>\n</ul>\n<p><strong>What We Offer</strong></p>\n<ul>\n<li>Competitive salary and bonus structure</li>\n<li>Generous Equity</li>\n<li>Health: Competitive Healthcare program (Medical Provider: Blueshield of California 100% coverage for employee, 75% for dependents)</li>\n<li>Pension: 401K (6% matching)</li>\n<li>PTO: 18 days</li>\n<li>Transportation: Reimburse office parking charges, or $120/month for public transport</li>\n<li>Coaching: we offer Betterup coaching on a voluntary basis</li>\n<li>Sport: $120/month reimbursement for gym membership</li>\n<li>Meal stipend: $400 monthly allowance for meals (solution might evolve as we grow bigger)</li>\n<li>Visa sponsorship</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_fe6b2de2-36b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral","sameAs":"https://www.mistral.ai/","logo":"https://logos.yubhub.co/mistral.ai.png"},"x-apply-url":"https://jobs.lever.co/mistral/7b20d2c8-d5a7-4efd-a13e-05d920ec5985","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","PyTorch","JAX","Rust","Go","Java","Ray","Kubernetes","large language models","distributed systems","MLOps"],"x-skills-preferred":["training large transformer models","fine-tuning","evaluation and deployment","audio input/out","NLP"],"datePosted":"2026-04-17T12:45:59.717Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Palo Alto"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, JAX, Rust, Go, Java, Ray, Kubernetes, large language models, distributed systems, MLOps, training large transformer models, fine-tuning, evaluation and deployment, audio input/out, NLP"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c63160d7-3af"},"title":"Senior Machine Learning Engineer","description":"<p>Join us on this thrilling journey to revolutionize the workforce with AI. As a Senior Machine Learning Engineer at Cresta, you will play a key role in shaping the future of work.</p>\n<p>At Cresta, we are on a mission to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. Our platform combines the best of AI and human intelligence to help contact centers discover customer insights and behavioural best practices, automate conversations and inefficient processes, and empower every team member to work smarter and faster.</p>\n<p>As a Senior Machine Learning Engineer, you will lead the design and development of Cresta&#39;s next-generation AI Agents and Agentic Assist systems, defining system architecture and core modeling approaches. You will architect intelligent, multi-step agent workflows that combine real-time guidance, knowledge retrieval, reasoning, summarization, and automated actions into cohesive production systems.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Lead the design and development of Cresta&#39;s next-generation AI Agents and Agentic Assist systems, defining system architecture and core modeling approaches.</li>\n<li>Architect intelligent, multi-step agent workflows that combine real-time guidance, knowledge retrieval, reasoning, summarization, and automated actions into cohesive production systems.</li>\n<li>Design, deploy, and optimize LLM-powered systems, including Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration, and domain-adapted models.</li>\n<li>Improve reasoning, planning, and tool-use capabilities in real-world AI applications.</li>\n<li>Develop evaluation strategies for complex, non-deterministic systems, including offline benchmarking, online experimentation, and LLM-as-a-judge methodologies.</li>\n<li>Diagnose and mitigate real-world failure modes such as hallucinations, retrieval errors, tool misuse, prompt brittleness, and multi-step reasoning breakdowns.</li>\n<li>Define and measure quality metrics (e.g., accuracy, faithfulness, task completion, latency, cost, robustness) to improve system reliability and performance.</li>\n<li>Optimize AI systems for scalability, latency, security, and cost efficiency in production environments.</li>\n<li>Collaborate cross-functionally with product, frontend, and backend teams to integrate AI capabilities seamlessly into Cresta&#39;s platform.</li>\n<li>Mentor engineers, contribute to technical strategy, and help shape the roadmap for Cresta&#39;s AI systems.</li>\n</ul>\n<p>Qualifications:</p>\n<ul>\n<li>Bachelor&#39;s degree in Computer Science, Mathematics, or a related field; Master&#39;s or Ph.D. preferred.</li>\n<li>5–8+ years of industry experience building and deploying machine learning systems in production, including significant experience working with LLMs.</li>\n<li>Strong expertise in NLP, Generative AI, transformer architectures, embeddings, and retrieval systems.</li>\n<li>Proven experience designing and deploying Retrieval-Augmented Generation (RAG) systems in enterprise environments.</li>\n<li>Experience building and evaluating complex agentic or multi-step LLM workflows.</li>\n<li>Strong knowledge of modern ML frameworks and tools (e.g., PyTorch, TensorFlow, Hugging Face) and distributed/cloud-based infrastructure.</li>\n<li>Demonstrated ability to optimize real-time ML systems for performance, scalability, and reliability.</li>\n<li>Strong technical leadership skills, with the ability to influence cross-functional decisions and raise the engineering bar.</li>\n</ul>\n<p>Perks &amp; Benefits:</p>\n<ul>\n<li>We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family&#39;s needs.</li>\n<li>Paid parental leave to support you and your family.</li>\n<li>Monthly Health &amp; Wellness allowance.</li>\n<li>Work from home office stipend to help you succeed in a remote environment.</li>\n<li>Lunch reimbursement for in-office employees.</li>\n<li>PTO: 3 weeks in Canada.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_c63160d7-3af","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Cresta","sameAs":"https://www.cresta.ai/","logo":"https://logos.yubhub.co/cresta.ai.png"},"x-apply-url":"https://job-boards.greenhouse.io/cresta/jobs/4249943008","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["NLP","Generative AI","Transformer architectures","Embeddings","Retrieval systems","PyTorch","TensorFlow","Hugging Face","Distributed/cloud-based infrastructure"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:27:30.020Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Canada (Remote)"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"NLP, Generative AI, Transformer architectures, Embeddings, Retrieval systems, PyTorch, TensorFlow, Hugging Face, Distributed/cloud-based infrastructure"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_5c28c97d-fc5"},"title":"Member of Technical Staff - Image / Video Generation","description":"<p><strong>Job Title</strong></p>\n<p>Member of Technical Staff - Image / Video Generation</p>\n<p><strong>Job Description</strong></p>\n<p>We&#39;re the team behind Latent Diffusion, Stable Diffusion, and FLUX,foundational technologies that changed how the world creates images and video. We&#39;re creating the generative models that power how people make images and video,tools used by millions of creators, developers, and businesses worldwide. Our FLUX models are among the most advanced in the world, and we’re just getting started.</p>\n<p><strong>Why This Role</strong></p>\n<p>You&#39;ll train large-scale diffusion models for image and video generation, exploring new approaches while maintaining the rigor that helps us distinguish meaningful progress from incremental tweaks. This isn&#39;t about following established recipes,it&#39;s about running the experiments that clarify which architectural choices matter and which are less impactful.</p>\n<p><strong>What You’ll Work On</strong></p>\n<ul>\n<li>Trains large-scale diffusion transformer models for image and video data, working at the scale where intuitions break and empirical evidence matters</li>\n<li>Rigorously ablates design choices,running experiments that isolate variables, control for confounds, and produce insights you can actually trust,then communicating those results to shape our research direction</li>\n<li>Reasons about the speed-quality tradeoffs of neural network architectures in production settings where both constraints matter simultaneously</li>\n<li>Fine-tunes diffusion models for specialized applications like image and video upscalers, inpainting/outpainting models, and other tasks where general-purpose models aren&#39;t enough</li>\n</ul>\n<p><strong>What We’re Looking For</strong></p>\n<ul>\n<li>You&#39;ve trained large-scale diffusion models and developed strong intuitions about what matters. You know that at research scale, every design choice has tradeoffs, and the only way to know which ones are worth making is through careful ablation. You&#39;re comfortable debugging distributed training issues and presenting research findings to the team.</li>\n</ul>\n<p><strong>Required Skills</strong></p>\n<ul>\n<li>Hands-on experience training large-scale diffusion models for image and video data, with practical knowledge of common failure modes and what matters most in training</li>\n<li>Experience fine-tuning diffusion models for specialized applications,upscalers, inpainting, outpainting, or other tasks where understanding the domain matters as much as understanding the architecture</li>\n<li>Deep understanding of how to effectively evaluate image and video generative models,knowing which metrics correlate with quality and which are just convenient proxies</li>\n<li>Strong proficiency in PyTorch, transformer architectures, and the full ecosystem of modern deep learning</li>\n<li>Solid understanding of distributed training techniques,FSDP, low precision training, model parallelism,because our models don&#39;t fit on one GPU and training decisions impact research outcomes</li>\n</ul>\n<p><strong>Preferred Skills</strong></p>\n<ul>\n<li>Experience writing forward and backward Triton kernels and ensuring their correctness while considering floating point errors</li>\n<li>Proficiency with profiling, debugging, and optimizing single and multi-GPU operations using tools like Nsight or stack trace viewers</li>\n<li>Know the performance characteristics of different architectural choices at scale</li>\n<li>Have published research that contributed to how people think about generative models</li>\n</ul>\n<p><strong>How We Work Together</strong></p>\n<p>We’re a distributed team with real offices that people actually use. Depending on your role, you’ll either join us in Freiburg or SF at least 2 days a week (or one full week every other week), or work remotely with a monthly in-person week to stay connected. We’ll cover reasonable travel costs to make this possible. We think in-person time matters, and we’ve structured things to make it accessible to all. We’ll discuss what this will look like for the role during our interview process.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_5c28c97d-fc5","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Black Forest Labs","sameAs":"https://www.blackforestlabs.com/","logo":"https://logos.yubhub.co/blackforestlabs.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/blackforestlabs/jobs/4132217008","x-work-arrangement":"hybrid","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["large-scale diffusion models","image and video data","PyTorch","transformer architectures","distributed training techniques"],"x-skills-preferred":["writing forward and backward Triton kernels","profiling, debugging, and optimizing single and multi-GPU operations","published research on generative models"],"datePosted":"2026-04-17T12:25:33.116Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Freiburg (Germany)"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"large-scale diffusion models, image and video data, PyTorch, transformer architectures, distributed training techniques, writing forward and backward Triton kernels, profiling, debugging, and optimizing single and multi-GPU operations, published research on generative models"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_15a14079-125"},"title":"AI/ML Engineering Manager, Payment Intelligence","description":"<p>Job Title: AI/ML Engineering Manager, Payment Intelligence</p>\n<p>Job Description:</p>\n<p>Stripe&#39;s mission is to accelerate global economic and technological development. We handle over $1.4T in payments volume per year, which is roughly 1.3% of the world&#39;s GDP.</p>\n<p>As an AI/ML Engineering Manager, you will oversee three critical teams within PayIntel, driving the strategic direction and execution for how Payments, and Stripe more generally, adopts AI, and how our suite of performance products leverage ML/AI to provide a consistent experience that generates revenue for Stripe.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Lead the development of our decisioning platform, ensuring that ML/AI decisions are consistent across the lifecycle of a payment regardless of which product makes those decisions.</li>\n<li>Collaborate with the ML Foundations team to develop and deploy Stripe&#39;s Foundation Model to risk, conversion and growth opportunities in Payments.</li>\n<li>Extend our performance analytics, observability, and risk management capabilities across Stripe so that users have a consistently high quality performance experience for cost, revenue, and risk across Stripe.</li>\n<li>Expand our Payments Analytics solution to ensure that users are fully aware of performance opportunities and can take full advantage of our suite of products to automate improvements.</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>10+ years of experience building and shipping ML models that power AI/ML product features, with a strong emphasis on modern technologies such as DNNs, Transformers, and Foundation Models.</li>\n<li>5+ years of experience managing and developing a team of managers, fostering their growth and ensuring alignment with strategic objectives.</li>\n<li>A strong builder mentality, with the ability to define a team&#39;s charter and lead the development of complex systems from scratch.</li>\n<li>Proven ability to shepherd large, complex projects and drive transformational change in an organization and with partners that depend on your team&#39;s platform services.</li>\n<li>Deep passion for solving really interesting problems, willingness to experiment, engage with customers directly to understand how well our solutions are working, and to build deep knowledge about performance that drives impact across the company.</li>\n</ul>\n<p>Preferred Qualifications:</p>\n<ul>\n<li>Experience with a large-scale, data-rich product in a domain such as payments, commerce, search, or social media.</li>\n<li>Knowledge of the challenges and opportunities in applying ML to fraud prevention, consumer intelligence, or financial services.</li>\n<li>Experience building platforms that accelerate service adoption outside your organization with little maintainability overhead.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_15a14079-125","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Stripe","sameAs":"https://stripe.com/","logo":"https://logos.yubhub.co/stripe.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/stripe/jobs/7286376","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Machine Learning","Artificial Intelligence","Data Science","Python","DNNs","Transformers","Foundation Models"],"x-skills-preferred":["Payments","Commerce","Search","Social Media","Fraud Prevention","Consumer Intelligence"],"datePosted":"2026-03-31T17:59:33.783Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"US-SF, US-NYC, US-SEA"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Finance","skills":"Machine Learning, Artificial Intelligence, Data Science, Python, DNNs, Transformers, Foundation Models, Payments, Commerce, Search, Social Media, Fraud Prevention, Consumer Intelligence"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_dd6ebd20-17d"},"title":"Research Scientist, Gemini Diffusion","description":"<p>We&#39;re looking for a Research Scientist to join our team in London and help us accelerate our mission. As a Research Scientist, you will apply your deep scientific knowledge and research skills to advance paradigm-shifting research at a large scale. You will be at the heart of our efforts to deliver step-changes in the capabilities of our frontier models, with a significant focus on our Gemini Diffusion project.</p>\n<p>Your work may involve brainstorming new disruptive ideas that could become the next generation of frontier AI models, particularly within the text diffusion space. You will prototype and develop these ideas with the rest of the team, contributing directly to Gemini Diffusion research. You will solve key research challenges by designing and executing experimental research on text diffusion models, sharing analyses, and proposing next steps. You will rigorously validate the theoretical and practical impact of our work at a large scale. You will work collaboratively with other Generative AI teams to move the technologies we develop out of the lab and into production. You will advance the fundamental architecture, algorithmic design, and capabilities of large-scale diffusion models. You will bring deep scientific expertise into our projects, sharing your insights and knowledge with other researchers and engineers.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_dd6ebd20-17d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Google DeepMind","sameAs":"https://deepmind.com/","logo":"https://logos.yubhub.co/deepmind.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/deepmind/jobs/7700399","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Advanced degree in computer science, electrical engineering, science, mathematics, or equivalent experience","Academic research experience in machine learning, publications, or research experience in related fields","Experience with some or all LLMs, Transformers, Diffusion models, Text diffusion, Large-scale distributed training","Strong communication skills (via discussion, presentation, technical and research writing, whiteboarding, etc.)","Programming experience, particularly with Python-based scientific libraries such as Numpy, Scipy, JAX, PyTorch, or TensorFlow"],"x-skills-preferred":["A track record of building software, either in open source or as part of a company product or research papers","Large-scale system design, distributed systems","Distributed computation for ML, especially in the context of accelerators (e.g., sharding, multi-host computation)","C++ or broader programming experience","Data engineering and visualisation"],"datePosted":"2026-03-16T14:39:03.737Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Advanced degree in computer science, electrical engineering, science, mathematics, or equivalent experience, Academic research experience in machine learning, publications, or research experience in related fields, Experience with some or all LLMs, Transformers, Diffusion models, Text diffusion, Large-scale distributed training, Strong communication skills (via discussion, presentation, technical and research writing, whiteboarding, etc.), Programming experience, particularly with Python-based scientific libraries such as Numpy, Scipy, JAX, PyTorch, or TensorFlow, A track record of building software, either in open source or as part of a company product or research papers, Large-scale system design, distributed systems, Distributed computation for ML, especially in the context of accelerators (e.g., sharding, multi-host computation), C++ or broader programming experience, Data engineering and visualisation"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_1338e7d1-ad8"},"title":"Cloud Machine Learning Engineer","description":"<p>At Hugging Face, we&#39;re on a journey to democratize good AI. We are building the fastest growing platform for AI builders. We are looking for a Cloud Machine Learning engineer responsible to help build machine learning solutions used by millions leveraging cloud technologies.</p>\n<p>You will work on integrating Hugging Face&#39;s open-source libraries like Transformers and Diffusers, with major cloud platforms or managed SaaS solutions. This role involves bridging and integrating models with different cloud providers, ensuring the models meet expected performance, designing and developing easy-to-use, secure, and robust developer experiences and APIs for our users, writing technical documentation, examples and notebooks to demonstrate new features, and sharing and advocating your work and the results with the community.</p>\n<p>The ideal candidate will have deep experience building with Hugging Face Technologies, including Transformers, Diffusers, Accelerate, PEFT, Datasets, expertise in Deep Learning Framework, preferably PyTorch, optionally XLA understanding, strong knowledge of cloud platforms like AWS and services like Amazon SageMaker, EC2, S3, CloudWatch and/or Azure and GCP equivalents, experience in building MLOps pipelines for containerizing models and solutions with Docker, familiarity with Typescript, Rust, and MongoDB, Kubernetes are helpful, ability to write clear documentation, examples and definition and work across the full product development lifecycle, and bonus experience with Svelte &amp; TailwindCSS.</p>\n<p>We are actively working to build a culture that values diversity, equity, and inclusivity. We are intentionally building a workplace where people feel respected and supported—regardless of who you are or where you come from. We believe this is foundational to building a great company and community.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_1338e7d1-ad8","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Hugging Face","sameAs":"https://huggingface.co/"},"x-apply-url":"https://apply.workable.com/j/A3879724CD","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Deep experience building with Hugging Face Technologies, including Transformers, Diffusers, Accelerate, PEFT, Datasets","Expertise in Deep Learning Framework, preferably PyTorch, optionally XLA understanding","Strong knowledge of cloud platforms like AWS and services like Amazon SageMaker, EC2, S3, CloudWatch and/or Azure and GCP equivalents","Experience in building MLOps pipelines for containerizing models and solutions with Docker","Familiarity with Typescript, Rust, and MongoDB, Kubernetes are helpful"],"x-skills-preferred":["Bonus experience with Svelte & TailwindCSS"],"datePosted":"2026-03-10T11:32:29.200Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"United States"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Deep experience building with Hugging Face Technologies, including Transformers, Diffusers, Accelerate, PEFT, Datasets, Expertise in Deep Learning Framework, preferably PyTorch, optionally XLA understanding, Strong knowledge of cloud platforms like AWS and services like Amazon SageMaker, EC2, S3, CloudWatch and/or Azure and GCP equivalents, Experience in building MLOps pipelines for containerizing models and solutions with Docker, Familiarity with Typescript, Rust, and MongoDB, Kubernetes are helpful, Bonus experience with Svelte & TailwindCSS"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_af4253f8-57e"},"title":"Cloud Machine Learning Engineer - EMEA remote","description":"<p>At Hugging Face, we&#39;re on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 11 million users who collectively shared over 2M models, 700k datasets &amp; 600k apps. Our open-source libraries have more than 600k+ stars on Github. Hugging Face has become the most popular, community-driven project for training, sharing, and deploying the most advanced machine learning models.</p>\n<p>We are looking for a Cloud Machine Learning engineer responsible to help build machine learning solutions used by millions leveraging cloud technologies. You will work on integrating Hugging Face&#39;s open-source libraries like Transformers and Diffusers, with major cloud platforms or managed SaaS solutions.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Bridging and integrating 🤗 transformers/diffusers models with a different Cloud provider.</li>\n<li>Ensuring the above models meet the expected performance</li>\n<li>Designing &amp; Developing easy-to-use, secure, and robust Developer Experiences &amp; APIs for our users.</li>\n<li>Write technical documentation, examples and notebooks to demonstrate new features</li>\n<li>Sharing &amp; Advocating your work and the results with the community.</li>\n</ul>\n<p>About You\nYou&#39;ll enjoy working on this team if you have experience with and interest in deploying machine learning systems to production and build great developer experiences. The ideal candidate will have skills including:</p>\n<ul>\n<li>Deep experience building with Hugging Face Technologies, including Transformers, Diffusers, Accelerate, PEFT, Datasets</li>\n<li>Expertise in Deep Learning Framework, preferably PyTorch, optionally XLA understanding</li>\n<li>Strong knowledge of cloud platforms like AWS and services like Amazon SageMaker, EC2, S3, CloudWatch and/or Azure and GCP equivalents.</li>\n<li>Experience in building MLOps pipelines for containerizing models and solutions with Docker</li>\n<li>Familiarity with Typescript, Rust, and MongoDB, Kubernetes are helpful</li>\n<li>Ability to write clear documentation, examples and definition and work across the full product development lifecycle</li>\n<li>Bonus: Experience with Svelte &amp; TailwindCSS</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_af4253f8-57e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Hugging Face","sameAs":"https://huggingface.co/"},"x-apply-url":"https://apply.workable.com/j/0CE9E806CC","x-work-arrangement":"remote","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Deep experience building with Hugging Face Technologies, including Transformers, Diffusers, Accelerate, PEFT, Datasets","Expertise in Deep Learning Framework, preferably PyTorch, optionally XLA understanding","Strong knowledge of cloud platforms like AWS and services like Amazon SageMaker, EC2, S3, CloudWatch and/or Azure and GCP equivalents.","Experience in building MLOps pipelines for containerizing models and solutions with Docker","Familiarity with Typescript, Rust, and MongoDB, Kubernetes are helpful"],"x-skills-preferred":["Svelte & TailwindCSS"],"datePosted":"2026-03-10T11:32:17.703Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Deep experience building with Hugging Face Technologies, including Transformers, Diffusers, Accelerate, PEFT, Datasets, Expertise in Deep Learning Framework, preferably PyTorch, optionally XLA understanding, Strong knowledge of cloud platforms like AWS and services like Amazon SageMaker, EC2, S3, CloudWatch and/or Azure and GCP equivalents., Experience in building MLOps pipelines for containerizing models and solutions with Docker, Familiarity with Typescript, Rust, and MongoDB, Kubernetes are helpful, Svelte & TailwindCSS"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_66a96d8c-777"},"title":"AI Scientist","description":"<p>At Mistral, we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world.</p>\n<p>We are hiring experts in the training of large language models and distributed systems. Join us to be part of a pioneering company shaping the future of AI.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Research and develop novel methods to push the frontier of large language models</li>\n<li>Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech)</li>\n<li>Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale</li>\n<li>Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact</li>\n</ul>\n<p><strong>About You:</strong></p>\n<ul>\n<li>You are a highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java)</li>\n<li>You have hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes)</li>\n<li>You have high engineering competence. This means being able to design complex software and make it usable in production</li>\n<li>You are a self-starter, autonomous and a team player</li>\n</ul>\n<p><strong>Nice to Have:</strong></p>\n<ul>\n<li>You have hands-on experience with training large transformer models in a distributed fashion</li>\n<li>You are able to navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment</li>\n<li>You have a strong publication record in a relevant scientific domain</li>\n<li>Audio/Speech experience - audio input/out, NLP</li>\n</ul>\n<p><strong>What We Offer:</strong></p>\n<ul>\n<li>Competitive salary and bonus structure</li>\n<li>Generous Equity</li>\n<li>Health: Competitive Healthcare program (Medical Provider: Blueshield of California 100% coverage for employee, 75% for dependents)</li>\n<li>Pension: 401K (6% matching)</li>\n<li>PTO: 18 days</li>\n<li>Transportation: Reimburse office parking charges, or $120/month for public transport</li>\n<li>Coaching: we offer Betterup coaching on a voluntary basis</li>\n<li>Sport: $120/month reimbursement for gym membership</li>\n<li>Meal stipend: $400 monthly allowance for meals (solution might evolve as we grow bigger)</li>\n<li>Visa sponsorship</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_66a96d8c-777","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral","sameAs":"https://www.mistral.ai/"},"x-apply-url":"https://jobs.lever.co/mistral/7b20d2c8-d5a7-4efd-a13e-05d920ec5985","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","PyTorch","JAX","Rust","Go","Java","distributed systems","Ray","Kubernetes","large language models","transformer models"],"x-skills-preferred":["audio input/out","NLP","MLOps","fine-tuning","evaluation","deployment"],"datePosted":"2026-03-10T11:30:26.219Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Palo Alto"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, JAX, Rust, Go, Java, distributed systems, Ray, Kubernetes, large language models, transformer models, audio input/out, NLP, MLOps, fine-tuning, evaluation, deployment"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_89406e8e-f38"},"title":"Machine Learning Engineer, Open-Source Software","description":"<p>You will be in charge of open-sourcing state-of-the-art models, whilst maintaining and improving Mistral’s publicly available libraries. Your work is critical in helping turn research breakthroughs into tangible solutions and improve Mistral&#39;s open-source ecosystem.</p>\n<p>About the Open Source Software team\nOur OSS team is embedded in our Science team and works very closely with various engineering and marketing teams. All OSS team members can fluidly move on the production / research spectrum depending on where the needs are or where their interests lie</p>\n<p>Responsibilities\n• Releasing our models to open-source platforms and libraries, e.g., vLLM, GitHub, Hugging Face\n• Maintaining Mistral’s open-source libraries (mistral-common, mistral-finetune, mistral-inference)\n• Create and maintain tooling and services: both internal facing (internal research) and external facing (open-source libraries)\n• Implement and optimize open-source and internal libraries for performance and accuracy, ensuring production readiness and employing cutting-edge technology and innovative approaches\n• Collaborate with the open-source community (PyTorch, vLLM, Hugging Face)</p>\n<p>About you\n• Master’s degree in Computer Science, Machine Learning, Data Science, or a related field\n• Experience contributing to popular open-source libraries such as PyTorch, Tensorflow, JAX, vLLM, Transformers, Llama.cpp, ...\n• Passion for contributing to the open-source software ecosystem\n• Expert programming skills in Python, PyTorch, MLOps\n• Adaptable, proactive, and autonomous\n• Attention to detail and a drive to go the last mile to build almost perfect tools\n• Deep understanding of machine learning approaches, especially LLMs and algorithms\n• Low-ego, collaborative and have a real team player mindset</p>\n<p>Now, it would be ideal if you have:\n• Experience with training and fine-tuning large language models (e.g., distillation, supervised fine-tuning, policy optimization)\n• Experience working with Slurm\n• Worked with research teams before\n• Experience as a core-maintainer of a popular ML open-source library</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_89406e8e-f38","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral AI","sameAs":"https://mistral.ai"},"x-apply-url":"https://jobs.lever.co/mistral/ef4c26fc-3fdb-4dd2-a64e-95264ee769dd","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","PyTorch","MLOps","Machine Learning","Large Language Models","Slurm","Open-source libraries"],"x-skills-preferred":["vLLM","GitHub","Hugging Face","PyTorch","Tensorflow","JAX","Transformers","Llama.cpp"],"datePosted":"2026-03-10T11:30:04.700Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, MLOps, Machine Learning, Large Language Models, Slurm, Open-source libraries, vLLM, GitHub, Hugging Face, PyTorch, Tensorflow, JAX, Transformers, Llama.cpp"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_49653163-8a7"},"title":"Senior Open-Source Machine Learning Engineer, Computer Vision","description":"<p>At Hugging Face, we&#39;re on a journey to democratize good AI. We are building the fastest growing platform for AI builders.</p>\n<p>As an Open-Source ML engineer in Computer Vision, you will work mainly with existing open-source libraries, such as Transformers and Datasets to boost the support for vision or multi-modal models and datasets. You will bring your computer vision expertise to provide the best computer-vision tool stack in the machine learning ecosystem and work with us to provide the best, simplest, and most intuitive computer-vision library in the industry.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Work with existing open-source libraries to boost support for vision or multi-modal models and datasets.</li>\n<li>Bring computer vision expertise to provide the best computer-vision tool stack in the machine learning ecosystem.</li>\n<li>Collaborate with researchers, ML practitioners, and data scientists on a daily basis.</li>\n<li>Foster one of the most active machine learning communities, helping users contribute to and use the tools that you build.</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>Deep expertise in computer vision: object detection, segmentation, generative models, or multimodal systems.</li>\n<li>Strong open-source presence: You’ve contributed significantly to CV libraries (e.g., OpenCV, Detectron2, MMDetection, or Hugging Face’s own transformers/diffusers), as a Core-Contributor or maintainer.</li>\n<li>Scalability mindset: Experience optimizing models for production, deploying at scale, or improving inference efficiency.</li>\n<li>Collaboration &amp; mentorship: You enjoy working with cross-functional teams, reviewing PRs, and guiding junior contributors.</li>\n<li>Alignment with our mission: You believe in democratizing AI and want to empower millions of builders with state-of-the-art tools.</li>\n</ul>\n<p>If you love open-source, are passionate about the new development of Transformers models in computer vision, have experience building, optimizing, and training such models in PyTorch and/or TensorFlow, serving them in production, and want to contribute to one of the fastest-growing ML libraries, then we can&#39;t wait to see your application!</p>\n<p>If you&#39;re interested in joining us, but don&#39;t tick every box above, we still encourage you to apply! We&#39;re building a diverse team whose skills, experiences, and backgrounds complement one another. We&#39;re happy to consider where you might be able to make the biggest impact.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_49653163-8a7","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Hugging Face","sameAs":"https://huggingface.co/"},"x-apply-url":"https://apply.workable.com/j/ED25C4FEA1","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["computer vision","object detection","segmentation","generative models","multimodal systems","open-source libraries","Transformers","Datasets","PyTorch","TensorFlow"],"x-skills-preferred":[],"datePosted":"2026-03-10T11:28:30.604Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York, New York"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"computer vision, object detection, segmentation, generative models, multimodal systems, open-source libraries, Transformers, Datasets, PyTorch, TensorFlow"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_af311231-ebb"},"title":"Senior Open-Source Machine Learning Engineer, Computer Vision","description":"<p>At Hugging Face, we&#39;re on a journey to democratize good AI.</p>\n<p>We are building the fastest growing platform for AI builders with over 11 million users who collectively shared over 2M models, 700k datasets &amp; 600k apps.</p>\n<p>As an Open-Source ML engineer in Computer Vision, you will work mainly with existing open-source libraries, such as Transformers and Datasets to boost the support for vision or multi-modal models and datasets.</p>\n<p>You will bring your computer vision expertise to provide the best computer-vision tool stack in the machine learning ecosystem and work with us to provide the best, simplest, and most intuitive computer-vision library in the industry.</p>\n<p>You&#39;ll get to foster one of the most active machine learning communities, helping users contribute to and use the tools that you build.</p>\n<p>You&#39;ll interact with Researchers, ML practitioners, and data scientists on a daily basis through GitHub, our forums, or slack.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Deep expertise in computer vision: object detection, segmentation, generative models, or multimodal systems.</li>\n<li>Strong open-source presence: You’ve contributed significantly to CV libraries (e.g., OpenCV, Detectron2, MMDetection, or Hugging Face’s own transformers/diffusers), as a Core-Contributor or maintainer.</li>\n<li>Scalability mindset: Experience optimizing models for production, deploying at scale, or improving inference efficiency.</li>\n<li>Collaboration &amp; mentorship: You enjoy working with cross-functional teams, reviewing PRs, and guiding junior contributors.</li>\n<li>Alignment with our mission: You believe in democratizing AI and want to empower millions of builders with state-of-the-art tools.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Flexible working hours and remote options.</li>\n<li>Health, dental, and vision benefits for employees and their dependents.</li>\n<li>Parental leave and flexible paid time off.</li>\n<li>Reimbursement for relevant conferences, training, and education.</li>\n<li>Company equity as part of their compensation package.</li>\n</ul>\n<p><strong>What We Offer</strong></p>\n<ul>\n<li>Work with some of the smartest people in our industry.</li>\n<li>A bias for impact and a continuous growth mindset.</li>\n<li>Support for your well-being and career development.</li>\n<li>Opportunities to visit our offices in NYC and Paris.</li>\n<li>An outfitting of your workstation to ensure success.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_af311231-ebb","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Hugging Face","sameAs":"https://huggingface.co/"},"x-apply-url":"https://apply.workable.com/j/0F3FFE6E77","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["computer vision","object detection","segmentation","generative models","multimodal systems","open-source libraries","Transformers","Datasets","PyTorch","TensorFlow"],"x-skills-preferred":[],"datePosted":"2026-03-10T11:28:12.342Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"computer vision, object detection, segmentation, generative models, multimodal systems, open-source libraries, Transformers, Datasets, PyTorch, TensorFlow"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6ef094ae-1e3"},"title":"AI Scientist - Paris/London - Onsite or Hybrid or Remote","description":"<p>At Mistral, we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world.</p>\n<p>We are hiring experts in the training of large language models and distributed systems. Join us to be part of a pioneering company shaping the future of AI.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Research and develop novel methods to push the frontier of large language models</li>\n<li>Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech)</li>\n<li>Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale</li>\n<li>Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact</li>\n</ul>\n<p>About you:</p>\n<ul>\n<li>You are a highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java)</li>\n<li>You have hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes)</li>\n<li>You have high engineering competence. This means being able to design complex software and make it usable in production</li>\n<li>You are a self-starter, autonomous and a team player</li>\n</ul>\n<p>Now, it would be ideal if:</p>\n<ul>\n<li>You have hands-on experience with training large transformer models in a distributed fashion</li>\n<li>You are able to navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment</li>\n<li>You have a strong publication record in a relevant scientific domain</li>\n</ul>\n<p>Benefits:</p>\n<ul>\n<li>Competitive cash salary and equity</li>\n<li>Food: Daily lunch vouchers</li>\n<li>Sport: Monthly contribution to a Gympass subscription</li>\n<li>Transportation: Monthly contribution to a mobility pass</li>\n<li>Health: Full health insurance for you and your family</li>\n<li>Parental: Generous parental leave policy</li>\n</ul>\n<p>France:</p>\n<ul>\n<li>Competitive cash salary and equity</li>\n<li>Food: Daily lunch vouchers</li>\n<li>Sport: Monthly contribution to a Gympass subscription</li>\n<li>Transportation: Monthly contribution to a mobility pass</li>\n<li>Health: Full health insurance for you and your family</li>\n<li>Parental: Generous parental leave policy</li>\n</ul>\n<p>UK:</p>\n<ul>\n<li>Competitive cash salary and equity</li>\n<li>Insurance</li>\n<li>Transportation: Reimburse office parking charges, or 90GBP/month for public transport</li>\n<li>Sport: 90GBP/month reimbursement for gym membership</li>\n<li>Meal voucher: £200 monthly allowance for its meals</li>\n<li>Pension plan: SmartPension (percentages are 5% Employee &amp; 3% Employer)</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_6ef094ae-1e3","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral","sameAs":"https://www.mistral.ai/"},"x-apply-url":"https://jobs.lever.co/mistral/675b7f06-a76b-4144-af0c-4dd3282ef489","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","PyTorch","JAX","Rust","Go","Java","Ray","Kubernetes"],"x-skills-preferred":["training large transformer models in a distributed fashion","MLOps stack","fine-tuning","evaluation and deployment"],"datePosted":"2026-03-10T11:27:29.319Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, JAX, Rust, Go, Java, Ray, Kubernetes, training large transformer models in a distributed fashion, MLOps stack, fine-tuning, evaluation and deployment"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_36e31c5c-5d1"},"title":"Open-Source Machine Learning Engineer","description":"<p>At Hugging Face, we&#39;re on a journey to democratize good AI. As an open-source Machine Learning Engineer, you will work to improve the open-source machine learning ecosystem. You will mainly work with existing open-source libraries, such as Transformers, Datasets, or Accelerate, and you will interact with users and contributors of the broad open-source machine learning ecosystem.</p>\n<p>We&#39;ll brainstorm with you to put you in a position to do the work that interests you and that is impactful. You&#39;ll get to foster one of the most active machine learning communities, helping users contribute to and use the tools that you build. You&#39;ll interact with Researchers, ML practitioners and data scientists on a daily basis through GitHub, our forums, or slack.</p>\n<p>If you love open-source, are passionate about making complex technology more accessible, and want to contribute to one of the fastest-growing ML ecosystems, then we can&#39;t wait to see your application! If you&#39;re interested in joining us, but don&#39;t tick every box above, we still encourage you to apply! We&#39;re building a diverse team whose skills, experiences, and background complement one another.</p>\n<p>More about Hugging Face</p>\n<p>We are actively working to build a culture that values diversity, equity, and inclusivity. We are intentionally building a workplace where people feel respected and supported—regardless of who you are or where you come from. We believe this is foundational to building a great company and community.</p>\n<p>Requirements</p>\n<p>Please provide a cover letter mentioning why you would like to work in open-source at Hugging Face. We encourage you to mention your skills, potential expertise, and topics on which you would like to work.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_36e31c5c-5d1","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Hugging Face","sameAs":"https://huggingface.co/"},"x-apply-url":"https://apply.workable.com/j/56232F23CB","x-work-arrangement":"remote","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["open-source machine learning","Transformers","Datasets","Accelerate","GitHub","Python"],"x-skills-preferred":["machine learning","artificial intelligence","data science","software engineering"],"datePosted":"2026-03-10T11:27:26.461Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York, New York"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"open-source machine learning, Transformers, Datasets, Accelerate, GitHub, Python, machine learning, artificial intelligence, data science, software engineering"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_67fcb604-29e"},"title":"Applied AI, Evaluation Engineer","description":"<p>About Mistral AI</p>\n<p>At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.</p>\n<p>We are a global organisation with teams distributed between France, USA, UK, Germany, and Singapore. Our comprehensive AI platform meets enterprise needs, whether on-premises or in cloud environments.</p>\n<p>Our offerings include le Chat, the AI assistant for life and work.</p>\n<p>About The Job</p>\n<p>The Applied AI team is Mistral&#39;s customer-facing technical organisation. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact.</p>\n<p>As a first Evaluation Engineer, you&#39;ll design the methodology, build the infrastructure, and define what &#39;ready for production&#39; means across verticals and use cases. You will design and implement evaluation systems that help our customers understand model performance across their specific use cases, build robust evaluation infrastructure, and work closely with both research and customer-facing teams.</p>\n<p>Research builds evals for frontier capabilities but customers don&#39;t care about MMLU scores. We need in Applied AI evals and frameworks for customer reality domain-specific, risk-aware, production-grade. The kind that tell you whether your medical summarization model will hallucinate drug interactions, or whether your legal assistant will invent case citations.</p>\n<p>This role sits at the intersection of research, engineering, and solutions, you will play a critical cross role in measuring, understanding, and improving the capabilities of our models for our enterprise customers.</p>\n<p>Responsibilities</p>\n<ul>\n<li><p>Design and implement comprehensive evaluation frameworks to measure LLM capabilities across diverse customer use cases, including text generation, reasoning, code, and domain-specific applications</p>\n</li>\n<li><p>Build scalable evaluation infrastructure and pipelines that enable rapid, reproducible assessment of model performance</p>\n</li>\n<li><p>Develop novel evaluation methodologies to assess emerging capabilities or verticalized use cases (cybersecurity, finance, healthcare, etc.) and enable the Solutions (Deployment Strategist and Applied AI) on these topics</p>\n</li>\n<li><p>Create custom evaluation suites tailored to enterprise customers&#39; specific needs, working closely with them to understand their requirements and success criteria</p>\n</li>\n<li><p>Collaborate with research teams to translate evaluation insights into model improvements and training decisions</p>\n</li>\n<li><p>Partner with product teams to continuously improve our evaluation tooling based on customer feedback</p>\n</li>\n</ul>\n<p>How We Work in Applied AI</p>\n<ul>\n<li><p>We care about people and outputs</p>\n</li>\n<li><p>What matters is what you ship, not the time you spend on it</p>\n</li>\n<li><p>Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week</p>\n</li>\n<li><p>Always ask why. The best solutions come from deep understanding, not from copying what worked before</p>\n</li>\n<li><p>We say what we mean. Feedback is direct, timely, and given because we care</p>\n</li>\n<li><p>No politics. Low ego, high standards</p>\n</li>\n<li><p>We embrace an unstructured environment and find joy in it</p>\n</li>\n</ul>\n<p>About You</p>\n<ul>\n<li><p>You are fluent in English</p>\n</li>\n<li><p>3+ years of experience in ML evaluation, benchmarking for LLM or agentic systems</p>\n</li>\n<li><p>You have proven experience in AI or machine learning product implementation with APIs, back-end</p>\n</li>\n<li><p>You have deep understanding of concepts and algorithms underlying machine learning and LLMs</p>\n</li>\n<li><p>You have strong technical coding skills in Python</p>\n</li>\n</ul>\n<p>Ideally You Have:</p>\n<ul>\n<li><p>Contributions to open-source evaluation frameworks (e.g., LM Eval Harness, OpenAI Evals) or published research on LLM evaluation</p>\n</li>\n<li><p>Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager</p>\n</li>\n<li><p>Experience with ML frameworks (PyTorch, HuggingFace Transformers)</p>\n</li>\n</ul>\n<p>Benefits</p>\n<p>PTO: The CDI contract will be a &#39;Forfait 218 jours&#39;, corresponding to 25 days of holidays and on average 8 to 10 days of RTT days, and complete autonomy on working hours</p>\n<p>Health: Full health insurance coverage for you and your family</p>\n<p>Transportation: We offer a €600 annual mobility allowance. This package covers 50% of your public transportation costs and includes the Sustainable Mobility Allowance (FMD), encouraging eco-friendly travel options such as cycling or carpooling</p>\n<p>Food: Swile meal vouchers with 10,83€ per worked day, incl 60% offered by company</p>\n<p>Sport: Gymlib - sponsorship by Mistral of a significant part of the monthly fee (depending on the program you chose)</p>\n<p>Parental policy: 4 additional weeks for parents on top of what is offered by the French state</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_67fcb604-29e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral AI","sameAs":"https://mistral.ai"},"x-apply-url":"https://jobs.lever.co/mistral/e0db3860-0a80-47a8-958a-f8e62f3bb59c","x-work-arrangement":"onsite","x-experience-level":"entry","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["ML evaluation","benchmarking","LLM","agentic systems","AI","machine learning","APIs","back-end","Python","PyTorch","HuggingFace Transformers"],"x-skills-preferred":[],"datePosted":"2026-03-10T11:25:45.717Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"ML evaluation, benchmarking, LLM, agentic systems, AI, machine learning, APIs, back-end, Python, PyTorch, HuggingFace Transformers"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_1aefaf93-fe1"},"title":"AI Scientist","description":"<p>About Mistral AI</p>\n<p>At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.</p>\n<p>We are a global team with a presence in France, USA, UK, Germany, and Singapore. Our diverse workforce thrives in competitive environments and is committed to driving innovation.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Research and develop novel methods to push the frontier of large language models</li>\n<li>Work across use cases (e.g., reasoning, code, agents) and modalities (e.g., text, image, and speech)</li>\n<li>Build tooling and infrastructure to allow training, evaluation, and analysis of AI models at scale</li>\n<li>Work cross-functionally with other scientists, engineers, and product teams to ship AI systems that have a real-world impact</li>\n</ul>\n<p><strong>About You</strong></p>\n<ul>\n<li>You are a highly proficient software engineer in at least one programming language (Python or other, e.g., Rust, Go, Java)</li>\n<li>You have hands-on experience with AI frameworks (e.g., PyTorch, JAX) or distributed systems (e.g., Ray, Kubernetes)</li>\n<li>You have high engineering competence. This means being able to design complex software and make it usable in production</li>\n<li>You are a self-starter, autonomous, and a team player</li>\n</ul>\n<p><strong>Preferred Qualifications</strong></p>\n<ul>\n<li>You have hands-on experience with training large transformer models in a distributed fashion</li>\n<li>You are able to navigate the full MLOps stack, for instance, fine-tuning, evaluation, and deployment</li>\n<li>You have a strong publication record in a relevant scientific domain</li>\n</ul>\n<p>Benefits</p>\n<ul>\n<li>Competitive cash salary and equity</li>\n<li>Food: Monthly meal allowance</li>\n<li>Sport: Monthly contribution to a Gympass subscription</li>\n<li>Private pension plan</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_1aefaf93-fe1","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral AI","sameAs":"https://mistral.ai"},"x-apply-url":"https://jobs.lever.co/mistral/bedfc2aa-f1b6-4136-bd17-b3abe4c06120","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","PyTorch","JAX","Rust","Go","Java","Ray","Kubernetes"],"x-skills-preferred":["Training large transformer models in a distributed fashion","Navigating the full MLOps stack","Strong publication record in a relevant scientific domain"],"datePosted":"2026-03-10T11:23:24.820Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Zurich"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, JAX, Rust, Go, Java, Ray, Kubernetes, Training large transformer models in a distributed fashion, Navigating the full MLOps stack, Strong publication record in a relevant scientific domain"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_82ef5cbb-727"},"title":"AI Scientist","description":"<p>About Mistral AI</p>\n<p>At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.</p>\n<p>We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise as well as personal needs. Our offerings include Le Chat, La Plateforme, Mistral Code and Mistral Compute - a suite that brings frontier intelligence to end-users.</p>\n<p>Responsibilities</p>\n<p>• Research and develop novel methods to push the frontier of large language models\n• Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech)\n• Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale\n• Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact</p>\n<p>About You</p>\n<p>• You are a highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java)\n• You have hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes)\n• You have high engineering competence. This means being able to design complex software and make it usable in production\n• You are a self-starter, autonomous and a team player</p>\n<p>Now, it would be ideal if</p>\n<p>• You have hands-on experience with training large transformer models in a distributed fashion\n• You are able to navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment\n• You have a strong publication record in a relevant scientific domain</p>\n<p>Benefits</p>\n<p>• Competitive cash salary and equity\n• Food: Monthly meal allowance\n• Sport: Monthly contribution to a Gympass subscription\n• Private pension plan</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_82ef5cbb-727","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral AI","sameAs":"https://mistral.ai"},"x-apply-url":"https://jobs.lever.co/mistral/4e498cbf-151e-483a-b3f7-76ff64a22041","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["software engineer","AI frameworks","distributed systems","high engineering competence","self-starter","autonomous","team player"],"x-skills-preferred":["hands-on experience with training large transformer models in a distributed fashion","navigate the full MLOps stack","strong publication record in a relevant scientific domain"],"datePosted":"2026-03-10T11:23:03.376Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Warsaw"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"software engineer, AI frameworks, distributed systems, high engineering competence, self-starter, autonomous, team player, hands-on experience with training large transformer models in a distributed fashion, navigate the full MLOps stack, strong publication record in a relevant scientific domain"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_77b20c01-867"},"title":"AI Scientist - Audio","description":"<p>About Mistral</p>\n<p>At Mistral, we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world.</p>\n<p>We develop models for the enterprise and for consumers, focusing on delivering systems which can really change the way in which businesses operate and which can integrate into our daily lives. All while releasing frontier models open-source, for everyone to try and benefit.</p>\n<p>What will you do?</p>\n<ul>\n<li>Research and develop novel methods to push the frontier of large language models</li>\n<li>Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech)</li>\n<li>Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale</li>\n<li>Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact</li>\n</ul>\n<p>About you</p>\n<ul>\n<li>An expert in speech input/output methodologies (specific to audio)</li>\n<li>You are a highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java)</li>\n<li>You have hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes)</li>\n<li>You have high engineering competence. This means being able to design complex software and make it usable in production</li>\n<li>You are a self-starter, autonomous and a team player</li>\n</ul>\n<p>Now, it would be ideal if</p>\n<ul>\n<li>You have experience working with large-scale speech-language models</li>\n<li>You have hands-on experience with training large transformer models in a distributed fashion</li>\n<li>You can navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment</li>\n<li>You have a strong publication record in a relevant scientific domain</li>\n</ul>\n<p>Note that this is not an exhaustive or necessary list of requirements. Please consider applying if you believe you have the skills to contribute to Mistral&#39;s mission. We value profile and experience diversity.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_77b20c01-867","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral","sameAs":"https://www.mistral.ai/"},"x-apply-url":"https://jobs.lever.co/mistral/94173e13-3050-4044-862a-e8dfc2deda5e","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"Competitive cash salary and equity","x-skills-required":["speech input/output methodologies","Python","PyTorch","JAX","distributed systems","Ray","Kubernetes","high engineering competence"],"x-skills-preferred":["large-scale speech-language models","training large transformer models in a distributed fashion","MLOps stack","fine-tuning","evaluation","deployment"],"datePosted":"2026-03-10T11:22:35.126Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"speech input/output methodologies, Python, PyTorch, JAX, distributed systems, Ray, Kubernetes, high engineering competence, large-scale speech-language models, training large transformer models in a distributed fashion, MLOps stack, fine-tuning, evaluation, deployment"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6eec1f11-84c"},"title":"Senior Product Manager: Searchandizing","description":"<p><strong>About Us</strong></p>\n<p>Constructor is a U.S. based company that has been in the market since 2019, providing a next-generation platform for search and discovery in e-commerce. Our search engine is entirely invented in-house utilizing transformers and generative LLMs, and we use its core and personalization capabilities to power everything from search itself to recommendations to shopping agents.</p>\n<p><strong>About You</strong></p>\n<p>As the Product Manager for Searchandizing, you will lead a cross-functional team to transform powerful merchandising tools into a guided, intuitive workflow that empowers customers to curate shopping experiences according to business goals. You are a user experience advocate and empathetic problem solver who can step into the shoes of e-commerce merchandisers to translate complex business needs into ROI-focused solutions.</p>\n<p><strong>Job Description</strong></p>\n<p>Constructor is the only platform that delivers reinforcement-learning-based product discovery that delivers the right product to the right person at the right time in the right context. However, our customers need to feel in control. They need to adjust shopping experience on top of Constructor algorithms to support their business goals, brand positioning, and marketing strategies. As a Product Manager, you will lead the Searchandizing team in providing customers with advanced tools to flexibly curate shopping experiences that optimize net revenue on top of Constructor&#39;s algorithms.</p>\n<p><strong>What You Will Do</strong></p>\n<ul>\n<li>Develop and execute a comprehensive product strategy for Searchandizing, ensuring it drives Constructor business by solving for customer needs.</li>\n<li>Own the Searchandizing workflow, from identifying the intent and setting up goals to launching campaigns, reviewing their performance, and iterating.</li>\n<li>Solve the real jobs of e-commerce merchandisers, including launching new products, managing stock levels, and providing smooth shopping experience when landing onsite from external sources.</li>\n<li>Prove ROI of Searchandizing by driving net revenue for our customers.</li>\n<li>Work closely and build trust with customers to understand who are the key users, what is their work process, and what makes them successful.</li>\n<li>Keep track of the competition and deliver clear differentiation of Constructor merchandising controls.</li>\n<li>Develop a holistic vision for all the tools Constructor provides to curate shopping experience (merch rules, facet controls, synonyms, redirects, etc.) and introduce a clear framework for team ownership, structure, and growth.</li>\n<li>Collaborate with multiple product teams to provide holistic dashboard experience and synergy between manual curation and algorithmic optimizations.</li>\n<li>Lead and scale a cross-functional team of engineers and designers, while owning the full product cycle from discovery to prototyping, implementation, launching, enabling fellow teams and customers, and iterating on results.</li>\n<li>Communicate effectively at all levels to ensure wonderful experience for customers, prospects, GTM teams, and internal stakeholders, by setting the right expectations and providing regular updates on product strategy, roadmaps, and progress against key metrics.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>You are a user experience advocate with a track record of redesigning fragmented toolsets into single, guided workflows.</li>\n<li>You understand that a feature isn&#39;t &#39;done&#39; until it is intuitive and fits naturally into the user&#39;s everyday process.</li>\n<li>You are a problem solver, meaning you dig into root causes to understand that a customer request for &#39;more rules&#39; can actually mean a better way to launch new products or manage out-of-stock inventory.</li>\n<li>You are focused on ROI and understand that merchandisers&#39; success is measured not only by the amount of control they have but also by the net revenue they create working in tandem with Constructor algorithms, and you want your product to prove that value explicitly.</li>\n<li>You are empathetic to customers, acknowledging they often don&#39;t know the right answers and need guidance towards data-driven decisions.</li>\n<li>You are inspired to motivate cross-functional teams by advocating customer needs, managing technical complexity, and delegating responsibility.</li>\n<li>You feel confident about managing commitments and expectations from numerous internal and external stakeholders while ensuring strategic focus.</li>\n<li>You seek a fast-moving entrepreneurial environment and thrive in ever-evolving processes.</li>\n<li>You base decisions on data but are ready to take action when faced with uncertainty.</li>\n<li>You are excited to bring learnings from your experience to augment our product culture and processes.</li>\n<li>You have experience of working remotely and in agile software development with empowered cross-functional teams.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Unlimited vacation time - we strongly encourage all employees to take at least 3 weeks per year.</li>\n<li>Fully remote team - choose where you live.</li>\n<li>Work from home stipend - we want you to have the resources you need to set up your home office.</li>\n<li>Apple laptops provided for new employees.</li>\n<li>Training and development budget - refreshed each year for every employee.</li>\n<li>Maternity &amp; Paternity leave for qualified employees.</li>\n<li>Work with smart people who will help you grow and make a meaningful impact.</li>\n<li>Base salary: $90K - $135K USD, depending on knowledge, skills, experience, and interview results.</li>\n<li>Stock options - offered in addition to the base salary.</li>\n<li>Regular team offsites to connect and collaborate.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_6eec1f11-84c","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Constructor","sameAs":"https://apply.workable.com","logo":"https://logos.yubhub.co/j.com.png"},"x-apply-url":"https://apply.workable.com/j/5F90B1C9AB","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$90K - $135K USD","x-skills-required":["user experience","product strategy","cross-functional team management","agile software development","data-driven decision making","customer empathy","problem solving","ROI focus","technical complexity management","strategic focus"],"x-skills-preferred":["transformers","generative LLMs","reinforcement-learning-based product discovery","merchandising tools","guided workflow","intuitive user experience","data analysis","algorithmic optimization"],"datePosted":"2026-03-09T11:00:26.221Z","jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"user experience, product strategy, cross-functional team management, agile software development, data-driven decision making, customer empathy, problem solving, ROI focus, technical complexity management, strategic focus, transformers, generative LLMs, reinforcement-learning-based product discovery, merchandising tools, guided workflow, intuitive user experience, data analysis, algorithmic optimization","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":90000,"maxValue":135000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_703876d0-bf6"},"title":"Senior Machine Learning Engineer: Ranking","description":"<p><strong>About Us</strong></p>\n<p>Constructor is a U.S. based company that develops a next-generation platform for search and discovery in ecommerce, built to optimize for metrics like revenue, conversion rate, and profit. Our search engine is entirely invented in-house utilizing transformers and generative LLMs, and we use its core and personalization capabilities to power everything from search itself to recommendations to shopping agents.</p>\n<p><strong>About the Team</strong></p>\n<p>The Ranking team, within the Machine Learning chapter, plays a central role in implementing algorithms that optimize our customers&#39; business KPIs like revenue and conversion rates. We focus on metrics over features, supplying our ranking algorithms with powerful capabilities that bring value to our customers.</p>\n<p><strong>Role Details</strong></p>\n<p><strong>Design and Develop ML-Based Ranking Solutions</strong></p>\n<p>As a Machine Learning Engineer on the Ranking team, your primary focus will be to enhance the quality of our ranking systems, ensuring that search, browse, and autocomplete experiences are highly relevant, personalized, and diverse. You will work on building state-of-the-art ranking algorithms that improve user experience and drive critical business metrics such as conversion, user engagement, and revenue growth.</p>\n<p><strong>Improve Ranking Quality</strong></p>\n<p>You will analyze ranking performance and identify gaps in search, browse, and autocomplete experiences, focusing on relevance, personalization, attractiveness, diversification, and other quality signals.</p>\n<p><strong>Innovate and Optimize Ranking Algorithms</strong></p>\n<p>You will proactively propose new machine learning models, algorithms, and features to advance the ranking pipeline, improve ranking quality, and meet evolving business needs.</p>\n<p><strong>Collaboration with Cross-Functional Teams</strong></p>\n<p>You will collaborate with technical and non-technical business partners to develop / update ranking functionalities (both within and outside the team)</p>\n<p><strong>Requirements</strong></p>\n<p><strong>Hard Skills</strong></p>\n<ul>\n<li>At least 4 years of experience with Python for machine learning and backend development</li>\n<li>At least 4 years of experience developing, deploying, and maintaining machine learning models with a strong focus on ranking systems for search, recommendations, or similar applications</li>\n<li>Experience in large-scale ML model training, evaluation, and optimization, with a focus on real-time inference and serving</li>\n<li>Experience with big data frameworks such as Spark for processing large datasets and integrating them into ML pipelines</li>\n<li>Proficiency in using tools like SQL, PySpark, Pandas, and other frameworks to extract, manipulate, and analyze data</li>\n<li>Experience with data pipeline orchestration tools like Airflow or Luigi to manage and automate workflows for ML training and signal delivery</li>\n<li>Experience working on ranking algorithms that optimize metrics such as relevance, conversion rates, personalization, user engagement, RPV is a plus</li>\n</ul>\n<p><strong>Soft Skills</strong></p>\n<ul>\n<li>Experience collaborating in cross-functional teams</li>\n<li>Experience leading projects to success</li>\n<li>Excellent English communication skills</li>\n<li>Enjoy helping others around you grow as developers and be successful</li>\n<li>Pick up new ideas and technologies quickly, love learning and talking to others about them</li>\n<li>Love to experiment and use data and customer feedback to drive decision making</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Unlimited vacation time</li>\n<li>Fully remote team</li>\n<li>Work from home stipend</li>\n<li>Apple laptops provided for new employees</li>\n<li>Training and development budget for every employee, refreshed each year</li>\n<li>Maternity &amp; Paternity leave for qualified employees</li>\n<li>Work with smart people who will help you grow and make a meaningful impact</li>\n<li>Base salary: $80k–$120k USD, depending on knowledge, skills, experience, and interview results</li>\n<li>Stock options</li>\n<li>Regular team offsites to connect and collaborate</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_703876d0-bf6","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Constructor","sameAs":"https://apply.workable.com","logo":"https://logos.yubhub.co/j.com.png"},"x-apply-url":"https://apply.workable.com/j/C130DBB1DC","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$80k–$120k USD","x-skills-required":["Python","Machine learning","Backend development","Ranking systems","Search","Recommendations","Big data frameworks","Spark","SQL","PySpark","Pandas","Airflow","Luigi"],"x-skills-preferred":["Transformers","Generative LLMs","Personalization","User experience","Conversion","User engagement","Revenue growth"],"datePosted":"2026-03-09T10:59:16.198Z","jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Machine learning, Backend development, Ranking systems, Search, Recommendations, Big data frameworks, Spark, SQL, PySpark, Pandas, Airflow, Luigi, Transformers, Generative LLMs, Personalization, User experience, Conversion, User engagement, Revenue growth","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":80000,"maxValue":120000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f5d2ba7b-c41"},"title":"Sales Development Representative EMEA (German, Remote)","description":"<p>We are looking for a motivated and enthusiastic Sales Development Representative to join our team in EMEA and focus on the DACH region. As an SDR, you will work closely with a dedicated Enterprise Account Executive and Marketing team to generate leads, start high quality conversations and build a strong customer pipeline. This is an entry-level role with a clear growth path tailored to your goals, supported by training that will help you become a successful professional - whether you choose to continue in sales or pursue another career path at Constructor.</p>\n<p>You will work 90% remotely and 10% on-site at events, where you will engage with prospects and customers alongside the Constructor team. Our search engine is built to explicitly optimize for metrics like revenue, conversion rate, and profit, using transformers and generative LLMs.</p>\n<p>We are seeking self-starters with a passion for both technology and people. You will identify and engage the right prospects within target accounts through high-quality research and thoughtful outreach, focusing on relevance over volume. You will personalize every interaction by deeply understanding a prospect’s industry, role, challenges, and business priorities.</p>\n<p>You will initiate meaningful conversations that center on the customer’s needs, pains, and goals - rather than pitching our services upfront. You will act as a trusted first point of contact, representing our values. You will collaborate closely with Enterprise Account Executives and Marketing to ensure alignment on account strategy and messaging.</p>\n<p>You will share insights from prospect conversations to help refine our go-to-market approach and improve customer relevance. You will maintain accurate records of all outreach, research, and engagement in Salesforce, ensuring visibility and collaboration across the team. You will continuously experiment with messaging, channels, and approaches to improve resonance and conversion.</p>\n<p>Requirements include 1+ year(s) experience in sales or sales development, excellent verbal and written communication in English &amp; German, and basic comfort working with sales tools such as Salesforce, LinkedIn Sales Navigator and Outreach. You will be based in Europe, with the ability to work across EMEA time zones, and have a genuine interest in technology, ecommerce, and helping businesses solve complex challenges.</p>\n<p>Benefits include unlimited vacation time, a competitive compensation package including stock options, fully remote team, work from home stipend, Apple laptops provided for new employees, training and development budget for every employee, refreshed each year, maternity &amp; paternity leave for qualified employees, and work with smart people who will help you grow and make a meaningful impact.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_f5d2ba7b-c41","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Constructor","sameAs":"https://apply.workable.com","logo":"https://logos.yubhub.co/j.com.png"},"x-apply-url":"https://apply.workable.com/j/3B385237C7","x-work-arrangement":"remote","x-experience-level":"entry","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Sales Development","Salesforce","LinkedIn Sales Navigator","Outreach","English","German"],"x-skills-preferred":["Transformers","Generative LLMs","Ecommerce","Technology"],"datePosted":"2026-03-09T10:56:46.938Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Germany"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Sales","industry":"Technology","skills":"Sales Development, Salesforce, LinkedIn Sales Navigator, Outreach, English, German, Transformers, Generative LLMs, Ecommerce, Technology"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_183800c4-b3d"},"title":"Researcher, Frontier Cybersecurity Risks","description":"<p><strong>Compensation</strong></p>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p><strong>About the team</strong></p>\n<p>The Safety Systems org ensures that OpenAI’s most capable models can be responsibly developed and deployed. We build evaluations, safeguards, and safety frameworks that help our models behave as intended in real-world settings.</p>\n<p>The Preparedness team is an important part of the [Safety Systems](https://openai.com/safety/safety-systems) org at OpenAI, and is guided by OpenAI’s [Preparedness Framework](https://openai.com/index/updating-our-preparedness-framework/).</p>\n<p>Frontier AI models have the potential to benefit all of humanity, but also pose increasingly severe risks. To ensure that AI promotes positive change, the Preparedness team helps us prepare for the development of increasingly capable frontier AI models. This team is tasked with identifying, tracking, and preparing for catastrophic risks related to frontier AI models.</p>\n<p>The mission of the Preparedness team is to:</p>\n<ol>\n<li>Closely monitor and predict the evolving capabilities of frontier AI systems, with an eye towards risks whose impact could be catastrophic</li>\n</ol>\n<ol>\n<li>Ensure we have concrete procedures, infrastructure and partnerships to mitigate these risks and to safely handle the development of powerful AI systems</li>\n</ol>\n<p><strong>About the role</strong></p>\n<p>Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. As we push toward AGI, cybersecurity becomes one of the most important and urgent frontiers: the same systems that can accelerate productivity can also accelerate exploitation.</p>\n<p>As a Researcher for cybersecurity risks, you will help design and implement an end-to-end mitigation stack to reduce severe cyber misuse across OpenAI’s products. This role requires strong technical depth and close cross-functional collaboration to ensure safeguards are enforceable, scalable, and effective. You’ll contribute directly to building protections that remain robust as products, model capabilities, and attacker behaviors evolve.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Design and implement mitigation components for model-enabled cybersecurity misuse—spanning prevention, monitoring, detection, and enforcement—under the guidance of senior technical and risk leadership.</li>\n</ul>\n<ul>\n<li>Integrate safeguards across product surfaces in partnership with product and engineering teams, helping ensure protections are consistent, low-latency, and scale with usage and new model capabilities.</li>\n</ul>\n<ul>\n<li>Evaluate technical trade-offs within the cybersecurity risk domain (coverage, latency, model utility, and user privacy) and propose pragmatic, testable solutions.</li>\n</ul>\n<ul>\n<li>Collaborate closely with risk and threat modeling partners to align mitigation design with anticipated attacker behaviors and high-impact misuse scenarios.</li>\n</ul>\n<ul>\n<li>Execute rigorous testing and red-teaming workflows, helping stress-test the mitigation stack against evolving threats (e.g., novel exploits, tool-use chains, automated attack workflows) and across different product surfaces—then iterate based on findings.</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Have a passion for AI safety and are motivated to make cutting-edge AI models safer for real-world use.</li>\n</ul>\n<ul>\n<li>Bring demonstrated experience in deep learning and transformer models.</li>\n</ul>\n<ul>\n<li>Are proficient with frameworks such as PyTorch or TensorFlow.</li>\n</ul>\n<ul>\n<li>Possess a strong foundation in data structures, algorithms, and software engineering principles.</li>\n</ul>\n<ul>\n<li>Are familiar with methods for training and fine-tuning large language models, including distillation, supervised fine-tuning, and policy optimization.</li>\n</ul>\n<ul>\n<li>Excel at working collaboratively with cross-functional teams across research, security, policy, product, and engineering.</li>\n</ul>\n<ul>\n<li>Have significant experience designing and deploying technical safeguards for abuse prevention, detection, and enforcement at scale.</li>\n</ul>\n<ul>\n<li>(Nice to have) Bring background knowledge in cybersecurity or adjacent fields.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_183800c4-b3d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/97a7eeae-9625-4d00-874f-e50131f98369","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"Full time","x-salary-range":"Estimated Base Salary $295K – $445K","x-skills-required":["Deep learning","Transformer models","PyTorch","TensorFlow","Data structures","Algorithms","Software engineering principles","Large language models","Abuse prevention","Detection","Enforcement"],"x-skills-preferred":["Cybersecurity","Adjacent fields"],"datePosted":"2026-03-08T22:17:00.637Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Deep learning, Transformer models, PyTorch, TensorFlow, Data structures, Algorithms, Software engineering principles, Large language models, Abuse prevention, Detection, Enforcement, Cybersecurity, Adjacent fields","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":295000,"maxValue":445000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b50d0ec9-1d8"},"title":"Engineering Manager, ML Acceleration","description":"<p><strong>About Anthropic</strong></p>\n<p>Anthropic&#39;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p>\n<p><strong>About the role:</strong></p>\n<p>Anthropic&#39;s performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training. As an Engineering Manager on these teams you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems. You also will help bring clarity, focus, and context to your teams in a fast paced, dynamic environment.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems</li>\n<li>Become familiar with the team’s technical stack enough to make targeted contributions as an individual contributor</li>\n<li>Manage day-to-day execution of the team&#39;s work</li>\n<li>Prioritize the team’s work and manage projects in a highly dynamic, fast paced environment</li>\n<li>Coach and support your reports in understanding, and pursuing, their professional growth</li>\n<li>Maintain a deep understanding of the team&#39;s technical work and its implications for AI safety</li>\n</ul>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Have 1+ years of management experience in a technical environment, particularly performance or distributed systems</li>\n<li>Have a background in machine learning, AI, or a similar related technical field</li>\n<li>Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development</li>\n<li>Excel at building strong relationships with stakeholders at all levels</li>\n<li>Are a quick learner, capable of understanding and contributing to discussions on complex technical topics</li>\n<li>Have experience managing teams through periods of rapid growth and change</li>\n<li>Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level of abstraction) to be effective</li>\n</ul>\n<p><strong>Strong candidates may also have experience with:</strong></p>\n<ul>\n<li>High performance, large-scale ML systems</li>\n<li>GPU/Accelerator programming</li>\n<li>ML framework internals</li>\n<li>OS internals</li>\n<li>Language modeling with transformers</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<p><strong>Education requirements:</strong> We require at least a Bachelor&#39;s degree in a related field or equivalent experience. <strong>Location-based hybrid policy:</strong> Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</p>\n<p><strong>Visa sponsorship:</strong></p>\n<p>We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</p>\n<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong></p>\n<p>Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work.</p>\n<p><strong>Your safety matters to us.</strong></p>\n<p>To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you&#39;re ever unsure about a communication, don&#39;t click any links—visit anthropic.com/careers directly for confirmed position openings.</p>\n<p><strong>How we&#39;re different</strong></p>\n<p>We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>\n<p>The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>\n<p><strong>Come work with us!</strong></p>\n<p>Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and paid time off, and a comprehensive benefits package.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_b50d0ec9-1d8","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4741104008","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$500,000 - $850,000 USD","x-skills-required":["Machine Learning","AI","Distributed Systems","High Performance Computing","GPU/Accelerator Programming","ML Framework Internals","OS Internals","Language Modeling with Transformers"],"x-skills-preferred":["High Performance, Large-Scale ML Systems","GPU/Accelerator Programming","ML Framework Internals","OS Internals","Language Modeling with Transformers"],"datePosted":"2026-03-08T13:58:59.618Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, AI, Distributed Systems, High Performance Computing, GPU/Accelerator Programming, ML Framework Internals, OS Internals, Language Modeling with Transformers, High Performance, Large-Scale ML Systems, GPU/Accelerator Programming, ML Framework Internals, OS Internals, Language Modeling with Transformers","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":500000,"maxValue":850000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_e4704a60-8d4"},"title":"Research Engineer / Research Scientist, Pre-training","description":"<p><strong>About Anthropic</strong></p>\n<p>Anthropic&#39;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p>\n<p><strong>About the team</strong></p>\n<p>We are seeking passionate Research Scientists and Engineers to join our growing Pre-training team in Zurich. We are involved in developing the next generation of large language models. The team primarily focuses on multimodal capabilities: giving LLMs the ability to understand and interact with modalities other than text.</p>\n<p>In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.</p>\n<p><strong>Responsibilities</strong></p>\n<p>In this role you will interact with many parts of the engineering and research stacks.</p>\n<ul>\n<li>Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development</li>\n</ul>\n<ul>\n<li>Independently lead small research projects while collaborating with team members on larger initiatives</li>\n</ul>\n<ul>\n<li>Design, run, and analyse scientific experiments to advance our understanding of large language models</li>\n</ul>\n<ul>\n<li>Optimise and scale our training infrastructure to improve efficiency and reliability</li>\n</ul>\n<ul>\n<li>Develop and improve dev tooling to enhance team productivity</li>\n</ul>\n<ul>\n<li>Contribute to the entire stack, from low-level optimisations to high-level model design</li>\n</ul>\n<p><strong>Qualifications &amp; Experience</strong></p>\n<p>We encourage you to apply even if you do not believe you meet every single criterion. Because we focus on so many areas, the team is looking for both experienced engineers and strong researchers, and encourage anyone along the researcher/engineer spectrum to apply.</p>\n<ul>\n<li>Degree (BA required, MS or PhD preferred) in Computer Science, Machine Learning, or a related field</li>\n</ul>\n<ul>\n<li>Strong software engineering skills with a proven track record of building complex systems</li>\n</ul>\n<ul>\n<li>Expertise in Python and deep learning frameworks</li>\n</ul>\n<ul>\n<li>Have worked on high-performance, large-scale ML systems, particularly in the context of language modelling</li>\n</ul>\n<ul>\n<li>Familiarity with ML Accelerators, Kubernetes, and large-scale data processing</li>\n</ul>\n<ul>\n<li>Strong problem-solving skills and a results-oriented mindset</li>\n</ul>\n<ul>\n<li>Excellent communication skills and ability to work in a collaborative environment</li>\n</ul>\n<p><strong>You&#39;ll thrive in this role if you</strong></p>\n<ul>\n<li>Have significant software engineering experience</li>\n</ul>\n<ul>\n<li>Are able to balance research goals with practical engineering constraints</li>\n</ul>\n<ul>\n<li>Are happy to take on tasks outside your job description to support the team</li>\n</ul>\n<ul>\n<li>Enjoy pair programming and collaborative work</li>\n</ul>\n<ul>\n<li>Are eager to learn more about machine learning research</li>\n</ul>\n<ul>\n<li>Are enthusiastic to work at an organisation that functions as a single, cohesive team pursuing large-scale AI research projects</li>\n</ul>\n<ul>\n<li>Have ambitious goals for AI safety and general progress in the next few years, and you’re excited to create the best outcomes over the long-term</li>\n</ul>\n<p><strong>Sample Projects</strong></p>\n<ul>\n<li>Optimising the throughput of novel attention mechanisms</li>\n</ul>\n<ul>\n<li>Proposing Transformer variants, and experimentally comparing their performance</li>\n</ul>\n<ul>\n<li>Preparing large-scale datasets for model consumption</li>\n</ul>\n<ul>\n<li>Scaling distributed training jobs to thousands of accelerators</li>\n</ul>\n<ul>\n<li>Designing fault tolerance strategies for training infrastructure</li>\n</ul>\n<ul>\n<li>Creating interactive visualisations of model internals, such as attention patterns</li>\n</ul>\n<p>If you&#39;re excited about pushing the boundaries of AI while prioritising safety and ethics, we want to hear from you!</p>\n<p><strong>Logistics</strong></p>\n<p><strong>Education requirements:</strong> We require at least a Bachelor&#39;s degree in a related field or equivalent experience. <strong>Location-based hybrid policy:</strong> Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</p>\n<p><strong>Visa sponsorship:</strong> We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</p>\n<p><strong>How we&#39;re different</strong></p>\n<p>We believe that the highest-impact work in AI safety and general progress in the next few years will be done by a single, cohesive team pursuing large-scale AI research projects. We&#39;re committed to creating a work environment that is inclusive, diverse, and supportive of our team members&#39; well-being and career growth.</p>\n<p><strong>Career Growth</strong></p>\n<p>We&#39;re committed to helping our team members grow and develop their careers. We offer opportunities for professional development, mentorship, and career advancement. We believe that our team members are the key to our success, and we&#39;re committed to supporting their growth and development.</p>\n<p><strong>Benefits</strong></p>\n<p>We offer a competitive salary and benefits package, including health insurance, retirement savings, and paid time off. We also offer a range of perks, including a generous parental leave policy, flexible work arrangements, and access to cutting-edge technology and tools.</p>\n<p><strong>How to Apply</strong></p>\n<p>If you&#39;re excited about joining our team and contributing to the development of safe, steerable, and trustworthy AI systems, please submit your application. We can&#39;t wait to hear from you!</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_e4704a60-8d4","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5135168008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"CHF280,000 - CHF680,000","x-skills-required":["Python","Deep learning frameworks","Machine learning","Software engineering","Kubernetes","ML Accelerators","Large-scale data processing"],"x-skills-preferred":["Transformer variants","Attention mechanisms","Distributed training jobs","Fault tolerance strategies","Interactive visualisations"],"datePosted":"2026-03-08T13:58:52.040Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Zürich"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Deep learning frameworks, Machine learning, Software engineering, Kubernetes, ML Accelerators, Large-scale data processing, Transformer variants, Attention mechanisms, Distributed training jobs, Fault tolerance strategies, Interactive visualisations","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":280000,"maxValue":680000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_20d39f2a-da8"},"title":"TPU Kernel Engineer","description":"<p><strong>About the Role</strong></p>\n<p>As a TPU Kernel Engineer, you&#39;ll be responsible for identifying and addressing performance issues across many different ML systems, including research, training, and inference. A significant portion of this work will involve designing and optimising kernels for the TPU. You will also provide feedback to researchers about how model changes impact performance.</p>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Have significant experience optimising ML systems for TPUs, GPUs, or other accelerators</li>\n<li>Are results-oriented, with a bias towards flexibility and impact</li>\n<li>Pick up slack, even if it goes outside your job description</li>\n<li>Enjoy pair programming (we love to pair!)</li>\n<li>Want to learn more about machine learning research</li>\n<li>Care about the societal impacts of your work</li>\n</ul>\n<p><strong>Strong candidates may also have experience with:</strong></p>\n<ul>\n<li>High performance, large-scale ML systems</li>\n<li>Designing and implementing kernels for TPUs or other ML accelerators</li>\n<li>Understanding accelerators at a deep level, e.g. a background in computer architecture</li>\n<li>ML framework internals</li>\n<li>Language modeling with transformers</li>\n</ul>\n<p><strong>Representative projects:</strong></p>\n<ul>\n<li>Implement low-latency, high-throughput sampling for large language models</li>\n<li>Adapt existing models for low-precision inference</li>\n<li>Build quantitative models of system performance</li>\n<li>Design and implement custom collective communication algorithms</li>\n<li>Debug kernel performance at the assembly level</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Education requirements: We require at least a Bachelor&#39;s degree in a related field or equivalent experience.</li>\n<li>Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</li>\n<li>Visa sponsorship: We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</li>\n</ul>\n<p><strong>We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work.</strong></p>\n<p><strong>Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you&#39;re ever unsure about a communication, don&#39;t click any links—visit anthropic.com/careers directly for confirmed position openings.</strong></p>\n<p><strong>How we&#39;re different</strong></p>\n<p>We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>\n<p>The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>\n<p><strong>Come work with us!</strong></p>\n<p>Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.</p>\n<p><strong>Guidance on Candidates&#39; AI Usage:</strong></p>\n<p>Learn about our policy for using AI in our application process</p>\n<p><strong>Apply for this job</strong></p>\n<ul>\n<li>indicates a required field</li>\n</ul>\n<p>First Name<em> Last Name</em> Email<em> Country</em> Phone* 244 results found No results found</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_20d39f2a-da8","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4720576008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$280,000 - $850,000USD","x-skills-required":["TPU","GPU","ML systems","kernel design","optimisation","pair programming","machine learning research","societal impacts"],"x-skills-preferred":["high performance","large-scale ML systems","computer architecture","ML framework internals","language modeling with transformers"],"datePosted":"2026-03-08T13:51:07.394Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"TPU, GPU, ML systems, kernel design, optimisation, pair programming, machine learning research, societal impacts, high performance, large-scale ML systems, computer architecture, ML framework internals, language modeling with transformers","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":280000,"maxValue":850000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_9c72720b-6af"},"title":"Research Engineer, Science of Scaling","description":"<p><strong>About Anthropic</strong></p>\n<p>Anthropic&#39;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p>\n<p><strong>About the role</strong></p>\n<p>Anthropic is seeking a Research Engineer/Scientist to join the Science of Scaling team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. You&#39;ll contribute across the entire stack, from low-level optimizations to high-level algorithm and experimental design, balancing research goals with practical engineering constraints.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Conduct research into the science of converting compute into intelligence</li>\n<li>Independently lead small research projects while collaborating with team members on larger initiatives</li>\n<li>Design, run, and analyse scientific experiments to advance our understanding of large language models</li>\n<li>Optimise training infrastructure to improve efficiency and reliability</li>\n<li>Develop dev tooling to enhance team productivity</li>\n</ul>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Have significant software engineering experience and a proven track record of building complex systems</li>\n<li>Hold an advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field</li>\n<li>Are proficient in Python and experienced with deep learning frameworks</li>\n<li>Are results-oriented with a bias towards flexibility and impact</li>\n<li>Enjoy pair programming and collaborative work, and are willing to take on tasks outside your job description to support the team</li>\n<li>View research and engineering as two sides of the same coin, seeking to understand all aspects of the research program to maximise impact</li>\n<li>Care about the societal impacts of your work and have ambitious goals for AI safety and general progress</li>\n</ul>\n<p><strong>Strong candidates may have:</strong></p>\n<ul>\n<li>Experience with JAX</li>\n<li>Experience with reinforcement learning</li>\n<li>Experience working on high-performance, large-scale ML systems</li>\n<li>Familiarity with accelerators, Kubernetes, and OS internals</li>\n<li>Experience with language modeling using transformer architectures</li>\n<li>Background in large-scale ETL processes</li>\n<li>Experience with distributed training at scale (thousands of accelerators)</li>\n</ul>\n<p><strong>Strong candidates need not have:</strong></p>\n<ul>\n<li>Experience in all of the above areas — we value breadth of interest and willingness to learn over checking every box</li>\n<li>Prior work specifically on language models or transformers; strong engineering fundamentals and ML knowledge transfer well</li>\n<li>An advanced degree — exceptional engineers with strong research instincts are equally encouraged to apply</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Education requirements: We require at least a Bachelor&#39;s degree in a related field or equivalent experience.</li>\n<li>Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</li>\n<li>Visa sponsorship: We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</li>\n</ul>\n<p><strong>We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work.</strong></p>\n<p><strong>Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you&#39;re ever unsure about a communication, don&#39;t click any links—visit anthropic.com/careers directly for confirmed position openings.</strong></p>\n<p><strong>How we&#39;re different</strong></p>\n<p>We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>\n<p>The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_9c72720b-6af","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5126127008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"£260,000 - £630,000GBP","x-skills-required":["software engineering","Python","deep learning frameworks","JAX","reinforcement learning","high-performance, large-scale ML systems","accelerators","Kubernetes","OS internals","language modeling using transformer architectures","large-scale ETL processes","distributed training at scale"],"x-skills-preferred":["JAX","reinforcement learning","high-performance, large-scale ML systems","accelerators","Kubernetes","OS internals","language modeling using transformer architectures","large-scale ETL processes","distributed training at scale"],"datePosted":"2026-03-08T13:50:55.750Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"software engineering, Python, deep learning frameworks, JAX, reinforcement learning, high-performance, large-scale ML systems, accelerators, Kubernetes, OS internals, language modeling using transformer architectures, large-scale ETL processes, distributed training at scale, JAX, reinforcement learning, high-performance, large-scale ML systems, accelerators, Kubernetes, OS internals, language modeling using transformer architectures, large-scale ETL processes, distributed training at scale","baseSalary":{"@type":"MonetaryAmount","currency":"GBP","value":{"@type":"QuantitativeValue","minValue":260000,"maxValue":630000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_390c02fb-0e8"},"title":"Research Engineer, Pretraining","description":"<p><strong>About Anthropic</strong></p>\n<p>Anthropic&#39;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p>\n<p><strong>Key Responsibilities:</strong></p>\n<ul>\n<li>Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development</li>\n</ul>\n<ul>\n<li>Independently lead small research projects while collaborating with team members on larger initiatives</li>\n</ul>\n<ul>\n<li>Design, run, and analyse scientific experiments to advance our understanding of large language models</li>\n</ul>\n<ul>\n<li>Optimise and scale our training infrastructure to improve efficiency and reliability</li>\n</ul>\n<ul>\n<li>Develop and improve dev tooling to enhance team productivity</li>\n</ul>\n<ul>\n<li>Contribute to the entire stack, from low-level optimisations to high-level model design</li>\n</ul>\n<p><strong>Qualifications:</strong></p>\n<ul>\n<li>Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field</li>\n</ul>\n<ul>\n<li>Strong software engineering skills with a proven track record of building complex systems</li>\n</ul>\n<ul>\n<li>Expertise in Python and experience with deep learning frameworks (PyTorch preferred)</li>\n</ul>\n<ul>\n<li>Familiarity with large-scale machine learning, particularly in the context of language models</li>\n</ul>\n<ul>\n<li>Ability to balance research goals with practical engineering constraints</li>\n</ul>\n<ul>\n<li>Strong problem-solving skills and a results-oriented mindset</li>\n</ul>\n<ul>\n<li>Excellent communication skills and ability to work in a collaborative environment</li>\n</ul>\n<ul>\n<li>Care about the societal impacts of your work</li>\n</ul>\n<p><strong>Preferred Experience:</strong></p>\n<ul>\n<li>Work on high-performance, large-scale ML systems</li>\n</ul>\n<ul>\n<li>Familiarity with GPUs, Kubernetes, and OS internals</li>\n</ul>\n<ul>\n<li>Experience with language modelling using transformer architectures</li>\n</ul>\n<ul>\n<li>Knowledge of reinforcement learning techniques</li>\n</ul>\n<ul>\n<li>Background in large-scale ETL processes</li>\n</ul>\n<p><strong>You&#39;ll thrive in this role if you:</strong></p>\n<ul>\n<li>Have significant software engineering experience</li>\n</ul>\n<ul>\n<li>Are results-oriented with a bias towards flexibility and impact</li>\n</ul>\n<ul>\n<li>Willingly take on tasks outside your job description to support the team</li>\n</ul>\n<ul>\n<li>Enjoy pair programming and collaborative work</li>\n</ul>\n<ul>\n<li>Are eager to learn more about machine learning research</li>\n</ul>\n<ul>\n<li>Are enthusiastic to work at an organisation that functions as a single, cohesive team pursuing large-scale AI research projects</li>\n</ul>\n<ul>\n<li>Are working to align state of the art models with human values and preferences, understand and interpret deep neural networks, or develop new models to support these areas of research</li>\n</ul>\n<ul>\n<li>View research and engineering as two sides of the same coin, and seek to understand all aspects of our research program as well as possible, to maximise the impact of your insights</li>\n</ul>\n<ul>\n<li>Have ambitious goals for AI safety and general progress in the next few years, and you’re working to create the best outcomes over the long-term.</li>\n</ul>\n<p><strong>Sample Projects:</strong></p>\n<ul>\n<li>Optimising the throughput of novel attention mechanisms</li>\n</ul>\n<ul>\n<li>Comparing compute efficiency of different Transformer variants</li>\n</ul>\n<ul>\n<li>Preparing large-scale datasets for efficient model consumption</li>\n</ul>\n<ul>\n<li>Scaling distributed training jobs to thousands of GPUs</li>\n</ul>\n<ul>\n<li>Designing fault tolerance strategies for our training infrastructure</li>\n</ul>\n<ul>\n<li>Creating interactive visualisations of model internals, such as attention patterns</li>\n</ul>\n<p><strong>Benefits:</strong></p>\n<p>At Anthropic, we are committed to fostering a diverse and inclusive workplace. We strongly encourage applications from candidates of all backgrounds, including those from underrepresented groups in tech.</p>\n<p><strong>Logistics:</strong></p>\n<ul>\n<li>Education requirements: We require at least a Bachelor&#39;s degree in a related field or equivalent experience.</li>\n</ul>\n<ul>\n<li>Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</li>\n</ul>\n<ul>\n<li>Visa sponsorship: We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</li>\n</ul>\n<ul>\n<li>We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work.</li>\n</ul>\n<ul>\n<li>Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from https://job-boards.greenhouse.io.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_390c02fb-0e8","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5119713008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"£260,000 - £630,000GBP","x-skills-required":["Python","Deep learning frameworks (PyTorch preferred)","Large-scale machine learning","Model architecture","Algorithms","Data processing","Optimizer development"],"x-skills-preferred":["GPU","Kubernetes","OS internals","Language modelling using transformer architectures","Reinforcement learning techniques","Background in large-scale ETL processes"],"datePosted":"2026-03-08T13:48:13.824Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Deep learning frameworks (PyTorch preferred), Large-scale machine learning, Model architecture, Algorithms, Data processing, Optimizer development, GPU, Kubernetes, OS internals, Language modelling using transformer architectures, Reinforcement learning techniques, Background in large-scale ETL processes","baseSalary":{"@type":"MonetaryAmount","currency":"GBP","value":{"@type":"QuantitativeValue","minValue":260000,"maxValue":630000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_716d3247-e3f"},"title":"ML/Research Engineer, Safeguards","description":"<p><strong>About Anthropic</strong></p>\n<p>Anthropic&#39;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p>\n<p><strong>About the role</strong></p>\n<p>We are looking for ML Engineers and Research Engineers to help detect and mitigate misuse of our AI systems. As a member of the Safeguards ML team, you will build systems that identify harmful use—from individual policy violations to sophisticated, coordinated attacks—and develop defenses that keep our products safe as capabilities advance. You will also work on systems that protect user wellbeing and ensure our models behave appropriately across a wide range of contexts. This work feeds directly into Anthropic&#39;s Responsible Scaling Policy commitments.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Develop classifiers to detect misuse and anomalous behavior at scale. This includes developing synthetic data pipelines for training classifiers and methods to automatically source representative evaluations to iterate on</li>\n<li>Build systems to monitor for harms that span multiple exchanges, such as coordinated cyber attacks and influence operations, and develop new methods for aggregating and analyzing signals across contexts</li>\n<li>Evaluate and improve the safety of agentic products—developing both threat models and environments to test for agentic risks, and developing and deploying mitigations for prompt injection attacks</li>\n<li>Conduct research on automated red-teaming, adversarial robustness, and other research that helps test for or find misuse</li>\n</ul>\n<p><strong>You may be a good fit if you</strong></p>\n<ul>\n<li>Have 4+ years of experience in ML engineering, research engineering, or applied research, in academia or industry</li>\n<li>Have proficiency in Python and experience building ML systems</li>\n<li>Are comfortable working across the research-to-deployment pipeline, from exploratory experiments to production systems</li>\n<li>Are worried about misuse risks of AI systems, and want to work to mitigate them</li>\n<li>Have strong communication skills and ability to explain complex technical concepts to non-technical stakeholders</li>\n</ul>\n<p><strong>Strong candidates may also have experience with</strong></p>\n<ul>\n<li>Language modeling and transformers</li>\n<li>Building classifiers, anomaly detection systems, or behavioral ML</li>\n<li>Adversarial machine learning or red-teaming</li>\n<li>Interpretability or probes</li>\n<li>Reinforcement learning</li>\n<li>High-performance, large-scale ML systems</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<p><strong>Education requirements:</strong> We require at least a Bachelor&#39;s degree in a related field or equivalent experience. <strong>Location-based hybrid policy:</strong> Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</p>\n<p><strong>Visa sponsorship</strong></p>\n<p>We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</p>\n<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong></p>\n<p>Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work.</p>\n<p><strong>Your safety matters to us.</strong></p>\n<p>To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you&#39;re ever unsure about a communication, don&#39;t click any links—visit anthropic.com/careers directly for confirmed position openings.</p>\n<p><strong>How we&#39;re different</strong></p>\n<p>We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>\n<p>The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>\n<p><strong>Come work with us!</strong></p>\n<p>Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_716d3247-e3f","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4949336008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$350,000 - $500,000USD","x-skills-required":["Python","Machine Learning","Research Engineering","Adversarial Machine Learning","Red-teaming","Interpretability","Probes","Reinforcement Learning","High-performance, large-scale ML systems"],"x-skills-preferred":["Language modeling and transformers","Building classifiers, anomaly detection systems, or behavioral ML"],"datePosted":"2026-03-08T13:46:45.711Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Machine Learning, Research Engineering, Adversarial Machine Learning, Red-teaming, Interpretability, Probes, Reinforcement Learning, High-performance, large-scale ML systems, Language modeling and transformers, Building classifiers, anomaly detection systems, or behavioral ML","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":350000,"maxValue":500000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_cd4d8376-407"},"title":"Research Engineer, Pre-training","description":"<p><strong>About Anthropic</strong></p>\n<p>Anthropic&#39;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p>\n<p><strong>Key Responsibilities:</strong></p>\n<ul>\n<li>Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development</li>\n<li>Independently lead small research projects while collaborating with team members on larger initiatives</li>\n<li>Design, run, and analyse scientific experiments to advance our understanding of large language models</li>\n<li>Optimise and scale our training infrastructure to improve efficiency and reliability</li>\n<li>Develop and improve dev tooling to enhance team productivity</li>\n<li>Contribute to the entire stack, from low-level optimisations to high-level model design</li>\n</ul>\n<p><strong>Qualifications:</strong></p>\n<ul>\n<li>Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field</li>\n<li>Strong software engineering skills with a proven track record of building complex systems</li>\n<li>Expertise in Python and experience with deep learning frameworks (PyTorch preferred)</li>\n<li>Familiarity with large-scale machine learning, particularly in the context of language models</li>\n<li>Ability to balance research goals with practical engineering constraints</li>\n<li>Strong problem-solving skills and a results-oriented mindset</li>\n<li>Excellent communication skills and ability to work in a collaborative environment</li>\n<li>Care about the societal impacts of your work</li>\n</ul>\n<p><strong>Preferred Experience:</strong></p>\n<ul>\n<li>Work on high-performance, large-scale ML systems</li>\n<li>Familiarity with GPUs, Kubernetes, and OS internals</li>\n<li>Experience with language modelling using transformer architectures</li>\n<li>Knowledge of reinforcement learning techniques</li>\n<li>Background in large-scale ETL processes</li>\n</ul>\n<p><strong>You&#39;ll thrive in this role if you:</strong></p>\n<ul>\n<li>Have significant software engineering experience</li>\n<li>Are results-oriented with a bias towards flexibility and impact</li>\n<li>Willingly take on tasks outside your job description to support the team</li>\n<li>Enjoy pair programming and collaborative work</li>\n<li>Are eager to learn more about machine learning research</li>\n<li>Are enthusiastic to work at an organisation that functions as a single, cohesive team pursuing large-scale AI research projects</li>\n<li>Are working to align state of the art models with human values and preferences, understand and interpret deep neural networks, or develop new models to support these areas of research</li>\n<li>View research and engineering as two sides of the same coin, and seek to understand all aspects of our research program as well as possible, to maximise the impact of your insights</li>\n<li>Have ambitious goals for AI safety and general progress in the next few years, and you’re working to create the best outcomes over the long-term.</li>\n</ul>\n<p><strong>Sample Projects:</strong></p>\n<ul>\n<li>Optimising the throughput of novel attention mechanisms</li>\n<li>Comparing compute efficiency of different Transformer variants</li>\n<li>Preparing large-scale datasets for efficient model consumption</li>\n<li>Scaling distributed training jobs to thousands of GPUs</li>\n<li>Designing fault tolerance strategies for our training infrastructure</li>\n<li>Creating interactive visualisations of model internals, such as attention patterns</li>\n</ul>\n<p><strong>At Anthropic, we are committed to fostering a diverse and inclusive workplace. We strongly encourage applications from candidates of all backgrounds, including those from underrepresented groups in tech.</strong></p>\n<p><strong>If you&#39;re excited about pushing the boundaries of AI while prioritising safety and ethics, we want to hear from you!</strong></p>\n<p><strong>The annual compensation range for this role is listed below.</strong></p>\n<p>For sales roles, the range provided is the role’s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</p>\n<p><strong>Annual Salary:</strong></p>\n<p>$350,000 - $850,000USD</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_cd4d8376-407","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4616971008","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$350,000 - $850,000USD","x-skills-required":["Python","Deep learning frameworks (PyTorch preferred)","Large-scale machine learning","Model architecture","Algorithms","Data processing","Optimizer development"],"x-skills-preferred":["GPU","Kubernetes","OS internals","Language modelling using transformer architectures","Reinforcement learning techniques","Background in large-scale ETL processes"],"datePosted":"2026-03-08T13:46:36.524Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, Seattle, WA, New York City, NY"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Deep learning frameworks (PyTorch preferred), Large-scale machine learning, Model architecture, Algorithms, Data processing, Optimizer development, GPU, Kubernetes, OS internals, Language modelling using transformer architectures, Reinforcement learning techniques, Background in large-scale ETL processes","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":350000,"maxValue":850000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6cc383e0-ff6"},"title":"ML Infrastructure Engineer, Safeguards","description":"<p><strong>About the role</strong></p>\n<p>We are seeking a Machine Learning Infrastructure Engineer to join our Safeguards organization, where you&#39;ll build and scale the critical infrastructure that powers our AI safety systems. You&#39;ll work at the intersection of machine learning, large-scale distributed systems, and AI safety, developing the platforms and tools that enable our safeguards to operate reliably at scale.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Design and build scalable ML infrastructure to support real-time and batch classifier and safety evaluations across our model ecosystem</li>\n<li>Build monitoring and observability tools to track model performance, data quality, and system health for safety-critical applications</li>\n<li>Collaborate with research teams to productionize safety research, translating experimental safety techniques into robust, scalable systems</li>\n<li>Optimize inference latency and throughput for real-time safety evaluations while maintaining high reliability standards</li>\n<li>Implement automated testing, deployment, and rollback systems for ML models in production safety applications</li>\n<li>Partner with Safeguards, Security, and Alignment teams to understand requirements and deliver infrastructure that meets safety and production needs</li>\n<li>Contribute to the development of internal tools and frameworks that accelerate safety research and deployment</li>\n</ul>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Have 5+ years of experience building production ML infrastructure, ideally in safety-critical domains like fraud detection, content moderation, or risk assessment</li>\n<li>Are proficient in Python and have experience with ML frameworks like PyTorch, TensorFlow, or JAX</li>\n<li>Have hands-on experience with cloud platforms (AWS, GCP) and container orchestration (Kubernetes)</li>\n<li>Understand distributed systems principles and have built systems that handle high-throughput, low-latency workloads</li>\n<li>Have experience with data engineering tools and building robust data pipelines (e.g., Spark, Airflow, streaming systems)</li>\n<li>Are results-oriented, with a bias towards reliability and impact in safety-critical systems</li>\n<li>Enjoy collaborating with researchers and translating cutting-edge research into production systems</li>\n<li>Care deeply about AI safety and the societal impacts of your work</li>\n</ul>\n<p><strong>Strong candidates may have experience with:</strong></p>\n<ul>\n<li>Working with large language models and modern transformer architectures</li>\n<li>Implementing A/B testing frameworks and experimentation infrastructure for ML systems</li>\n<li>Developing monitoring and alerting systems for ML model performance and data drift</li>\n<li>Building automated labeling systems and human-in-the-loop workflows</li>\n<li>Experience in trust &amp; safety, fraud prevention, or content moderation domains</li>\n<li>Knowledge of privacy-preserving ML techniques and compliance requirements</li>\n<li>Contributing to open-source ML infrastructure projects</li>\n</ul>\n<p><strong>Deadline to apply:</strong></p>\n<p>None. Applications will be reviewed on a rolling basis.</p>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Education requirements: We require at least a Bachelor&#39;s degree in a related field or equivalent experience.</li>\n<li>Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</li>\n<li>Visa sponsorship: We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</li>\n</ul>\n<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong></p>\n<p>Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work.</p>\n<p><strong>Your safety matters to us.</strong></p>\n<p>To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you&#39;re ever unsure about a communication, don&#39;t click any links—visit anthropic.com/careers directly for confirmed position openings.</p>\n<p><strong>How we&#39;re different</strong></p>\n<p>We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing the state of the art in AI safety and making a meaningful difference in the world.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_6cc383e0-ff6","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4778843008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$320,000 - $405,000 USD","x-skills-required":["Python","PyTorch","TensorFlow","JAX","AWS","GCP","Kubernetes","Spark","Airflow","streaming systems"],"x-skills-preferred":["large language models","modern transformer architectures","A/B testing frameworks","experimentation infrastructure","monitoring and alerting systems","automated labeling systems","human-in-the-loop workflows","trust & safety","fraud prevention","content moderation domains","privacy-preserving ML techniques","compliance requirements"],"datePosted":"2026-03-08T13:46:05.401Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, TensorFlow, JAX, AWS, GCP, Kubernetes, Spark, Airflow, streaming systems, large language models, modern transformer architectures, A/B testing frameworks, experimentation infrastructure, monitoring and alerting systems, automated labeling systems, human-in-the-loop workflows, trust & safety, fraud prevention, content moderation domains, privacy-preserving ML techniques, compliance requirements","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":320000,"maxValue":405000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_797f344d-f9f"},"title":"Performance Engineer","description":"<p><strong>About the role:</strong></p>\n<p>Running machine learning (ML) algorithms at our scale often requires solving novel systems problems. As a Performance Engineer, you&#39;ll be responsible for identifying these problems, and then developing systems that optimize the throughput and robustness of our largest distributed systems. Strong candidates here will have a track record of solving large-scale systems problems and will be excited to grow to become an expert in ML also.</p>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Have significant software engineering or machine learning experience, particularly at supercomputing scale</li>\n<li>Are results-oriented, with a bias towards flexibility and impact</li>\n<li>Pick up slack, even if it goes outside your job description</li>\n<li>Enjoy pair programming (we love to pair!)</li>\n<li>Want to learn more about machine learning research</li>\n<li>Care about the societal impacts of your work</li>\n</ul>\n<p><strong>Strong candidates may also have experience with:</strong></p>\n<ul>\n<li>High performance, large-scale ML systems</li>\n<li>GPU/Accelerator programming</li>\n<li>ML framework internals</li>\n<li>OS internals</li>\n<li>Language modeling with transformers</li>\n</ul>\n<p><strong>Representative projects:</strong></p>\n<ul>\n<li>Implement low-latency high-throughput sampling for large language models</li>\n<li>Implement GPU kernels to adapt our models to low-precision inference</li>\n<li>Write a custom load-balancing algorithm to optimize serving efficiency</li>\n<li>Build quantitative models of system performance</li>\n<li>Design and implement a fault-tolerant distributed system running with a complex network topology</li>\n<li>Debug kernel-level network latency spikes in a containerized environment</li>\n</ul>\n<p><strong>Deadline to apply:</strong></p>\n<p>None. Applications will be reviewed on a rolling basis.</p>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Education requirements: We require at least a Bachelor&#39;s degree in a related field or equivalent experience.</li>\n<li>Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</li>\n<li>Visa sponsorship: We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</li>\n</ul>\n<p><strong>We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work.</strong></p>\n<p><strong>Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you&#39;re ever unsure about a communication, don&#39;t click any links—visit anthropic.com/careers directly for confirmed position openings.</strong></p>\n<p><strong>How we&#39;re different</strong></p>\n<p>We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>\n<p>The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>\n<p><strong>Come work with us!</strong></p>\n<p>Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.</p>\n<p><strong>Guidance on Candidates&#39; AI Usage:</strong></p>\n<p>Learn about our policy for using AI in our application process</p>\n<p><strong>Apply for this job</strong></p>\n<ul>\n<li>indicates a required field</li>\n</ul>\n<p>First Name<em> Last Name</em> Email<em> Country</em> Phone* 244 results found No results found</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_797f344d-f9f","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4020350008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$280,000 - $850,000USD","x-skills-required":["software engineering","machine learning","GPU/Accelerator programming","ML framework internals","OS internals","language modeling with transformers"],"x-skills-preferred":["high performance, large-scale ML systems","fault-tolerant distributed systems","complex network topology","quantitative models of system performance"],"datePosted":"2026-03-08T13:45:53.165Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"software engineering, machine learning, GPU/Accelerator programming, ML framework internals, OS internals, language modeling with transformers, high performance, large-scale ML systems, fault-tolerant distributed systems, complex network topology, quantitative models of system performance","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":280000,"maxValue":850000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b376a3b3-b21"},"title":"Machine Learning Systems Engineer, Research Tools","description":"<p><strong>About the Role:</strong></p>\n<p>We are seeking an experienced Machine Learning Systems Engineer to join our Encodings and Tokenization team at Anthropic. This cross-functional role will be instrumental in developing and optimising the encodings and tokenization systems used throughout our Finetuning workflows. As a bridge between our Pretraining and Finetuning teams, you&#39;ll build critical infrastructure that directly impacts how our models learn from and interpret data. Your work will be foundational to Anthropic&#39;s research progress, enabling more efficient and effective training of our AI systems while ensuring they remain reliable, interpretable, and steerable.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Design, develop, and maintain tokenization systems used across Pretraining and Finetuning workflows</li>\n<li>Optimise encoding techniques to improve model training efficiency and performance</li>\n<li>Collaborate closely with research teams to understand their evolving needs around data representation</li>\n<li>Build infrastructure that enables researchers to experiment with novel tokenization approaches</li>\n<li>Implement systems for monitoring and debugging tokenization-related issues in the model training pipeline</li>\n<li>Create robust testing frameworks to validate tokenization systems across diverse languages and data types</li>\n<li>Identify and address bottlenecks in data processing pipelines related to tokenization</li>\n<li>Document systems thoroughly and communicate technical decisions clearly to stakeholders across teams</li>\n</ul>\n<p><strong>You May Be a Good Fit If You:</strong></p>\n<ul>\n<li>Have significant software engineering experience with demonstrated machine learning expertise</li>\n<li>Are comfortable navigating ambiguity and developing solutions in rapidly evolving research environments</li>\n<li>Can work independently while maintaining strong collaboration with cross-functional teams</li>\n<li>Are results-oriented, with a bias towards flexibility and impact</li>\n<li>Have experience with machine learning systems, data pipelines, or ML infrastructure</li>\n<li>Are proficient in Python and familiar with modern ML development practices</li>\n<li>Have strong analytical skills and can evaluate the impact of engineering changes on research outcomes</li>\n<li>Pick up slack, even if it goes outside your job description</li>\n<li>Enjoy pair programming (we love to pair!)</li>\n<li>Care about the societal impacts of your work and are committed to developing AI responsibly</li>\n</ul>\n<p><strong>Strong Candidates May Also Have Experience With:</strong></p>\n<ul>\n<li>Working with machine learning data processing pipelines</li>\n<li>Building or optimising data encodings for ML applications</li>\n<li>Implementing or working with BPE, WordPiece, or other tokenization algorithms</li>\n<li>Performance optimisation of ML data processing systems</li>\n<li>Multi-language tokenisation challenges and solutions</li>\n<li>Research environments where engineering directly enables scientific progress</li>\n<li>Distributed systems and parallel computing for ML workflows</li>\n<li>Large language models or other transformer-based architectures (not required)</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Education requirements: We require at least a Bachelor&#39;s degree in a related field or equivalent experience.</li>\n<li>Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</li>\n<li>Visa sponsorship: We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</li>\n</ul>\n<p><strong>How we&#39;re different</strong></p>\n<p>We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_b376a3b3-b21","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4952079008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$320,000 - $405,000 USD","x-skills-required":["Machine Learning","Software Engineering","Python","Data Pipelines","ML Infrastructure","Tokenization","Encoding","BPE","WordPiece"],"x-skills-preferred":["Distributed Systems","Parallel Computing","Large Language Models","Transformer-Based Architectures"],"datePosted":"2026-03-08T13:44:14.348Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, Software Engineering, Python, Data Pipelines, ML Infrastructure, Tokenization, Encoding, BPE, WordPiece, Distributed Systems, Parallel Computing, Large Language Models, Transformer-Based Architectures","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":320000,"maxValue":405000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_5897facf-31b"},"title":"Engineering Manager, Inference","description":"<p><strong>About the role:</strong></p>\n<p>Anthropic&#39;s performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training. As an Engineering Manager on these teams, you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems. You also will help bring clarity, focus, and context to your teams in a fast-paced, dynamic environment.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems</li>\n<li>Become familiar with the team&#39;s technical stack enough to make targeted contributions as an individual contributor</li>\n<li>Manage day-to-day execution of the team&#39;s work</li>\n<li>Prioritize the team&#39;s work and manage projects in a highly dynamic, fast-paced environment</li>\n<li>Coach and support your reports in understanding, and pursuing, their professional growth</li>\n<li>Maintain a deep understanding of the team&#39;s technical work and its implications for AI safety</li>\n</ul>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Have 1+ years of management experience in a technical environment, particularly performance or distributed systems</li>\n<li>Have a background in machine learning, AI, or a similar related technical field</li>\n<li>Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development</li>\n<li>Excel at building strong relationships with stakeholders at all levels</li>\n<li>Are a quick learner, capable of understanding and contributing to discussions on complex technical topics</li>\n<li>Have experience managing teams through periods of rapid growth and change</li>\n<li>Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you&#39;ll need to understand (at a high level of abstraction) to be effective</li>\n</ul>\n<p><strong>Strong candidates may also have experience with:</strong></p>\n<ul>\n<li>High performance, large-scale ML systems</li>\n<li>GPU/Accelerator programming</li>\n<li>ML framework internals</li>\n<li>OS internals</li>\n<li>Language modeling with transformers</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Education requirements: We require at least a Bachelor&#39;s degree in a related field or equivalent experience.</li>\n<li>Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</li>\n<li>Visa sponsorship: We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</li>\n</ul>\n<p><strong>How we&#39;re different</strong></p>\n<p>We believe that the highest-impact AI research will be big science. At Anthropic, we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>\n<p><strong>Come work with us!</strong></p>\n<p>Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave policies, and a dynamic and inclusive work environment.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_5897facf-31b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4741102008","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$425,000 - $560,000USD","x-skills-required":["machine learning","AI","performance systems","distributed systems","high performance","large-scale ML systems","GPU/Accelerator programming","ML framework internals","OS internals","language modeling with transformers"],"x-skills-preferred":["high performance","large-scale ML systems","GPU/Accelerator programming","ML framework internals","OS internals","language modeling with transformers"],"datePosted":"2026-03-08T13:43:30.101Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, AI, performance systems, distributed systems, high performance, large-scale ML systems, GPU/Accelerator programming, ML framework internals, OS internals, language modeling with transformers, high performance, large-scale ML systems, GPU/Accelerator programming, ML framework internals, OS internals, language modeling with transformers","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":425000,"maxValue":560000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_a21c0ab8-098"},"title":"Researcher, Training","description":"<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Department</strong></p>\n<p>Research</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$360K – $440K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong>About the Team</strong></p>\n<p>OpenAI&#39;s Training team is responsible for producing the large language models that power our research, our products, and ultimately bring us closer to AGI. Achieving this goal requires combining deep research into improving our current architecture, datasets and optimization techniques, alongside long-term bets aimed at improving the efficiency and capability of future generations of models. We are responsible for integrating these techniques and producing model artifacts used by the rest of the company, and ensuring that these models are world-class in every respect. Recent examples of artifacts with major contributions from our team include GPT4-Turbo, GPT-4o and o1-mini.</p>\n<p><strong>About the Role</strong></p>\n<p>As a member of the architecture team, you will push the frontier of architecture development for OpenAI&#39;s flagship models, enhancing intelligence, efficiency, and adding new capabilities.</p>\n<p>Ideal candidates have a deep understanding of LLM architectures, a sophisticated understanding of model inference, and a hands-on empirical approach. A good fit for this role will be equally happy coming up with a creative breakthrough, investing in strengthening a baseline, designing an eval, debugging a thorny regression, or tracking down a bottleneck.</p>\n<p>This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Design, prototype and scale up new architectures to improve model intelligence</li>\n<li>Execute and analyze experiments autonomously and collaboratively</li>\n<li>Study, debug, and optimize both model performance and computational performance</li>\n<li>Contribute to training and inference infrastructure</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Have experience landing contributions to major LLM training runs</li>\n<li>Can thoroughly evaluate and improve deep learning architectures in a self-directed fashion</li>\n<li>Are motivated by safely deploying LLMs in the real world</li>\n<li>Are well-versed in the state of the art transformer modifications for efficiency</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_a21c0ab8-098","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/97d3670c-e75a-4bb2-a235-171765f5f10e","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$360K – $440K • Offers Equity","x-skills-required":["Deep learning","Transformers","Model inference","Architecture development","Experiment design","Optimization techniques"],"x-skills-preferred":["LLM architectures","Model performance","Computational performance","Training and inference infrastructure"],"datePosted":"2026-03-06T18:36:46.181Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Deep learning, Transformers, Model inference, Architecture development, Experiment design, Optimization techniques, LLM architectures, Model performance, Computational performance, Training and inference infrastructure","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":360000,"maxValue":440000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_75ad55ca-61b"},"title":"Research Engineer / Research Scientist - Foundations Retrieval IC","description":"<p><strong>Job Posting</strong></p>\n<p><strong>Research Engineer / Research Scientist - Foundations Retrieval IC</strong></p>\n<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Department</strong></p>\n<p>Research</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$445K – $555K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong>About the Team</strong></p>\n<p>The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science.</p>\n<p><strong>About the Role</strong></p>\n<p>We’re looking for a researcher focused on our embedding retrieval efforts. You’ll work with a team of world-class research scientists and engineers developing foundational technology that enables models to retrieve and condition on the right information, at the right time. This includes designing new embedding training objectives, scalable vector store architectures, and dynamic indexing methods.</p>\n<p>This work will support retrieval across many OpenAI products and internal research efforts, with opportunities for scientific publication and deep technical impact.</p>\n<p>This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Tackle embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning.</li>\n</ul>\n<ul>\n<li>Collaborate with a team of researchers and engineers building end-to-end infrastructure for training, evaluating, and integrating embeddings into frontier models.</li>\n</ul>\n<ul>\n<li>Drive innovation in dense, sparse, and hybrid representation techniques, metric learning, and learning-to-retrieve systems.</li>\n</ul>\n<ul>\n<li>Collaborate closely with Pretraining, Inference, and other Research teams to integrate retrieval throughout the model lifecycle</li>\n</ul>\n<ul>\n<li>Contribute to OpenAI’s long-term vision of AI systems with memory and knowledge access capabilities rooted in learned representations.</li>\n</ul>\n<p><strong>You Might Thrive in This Role If You Have</strong></p>\n<ul>\n<li>Proven experience leading high-performance teams of researchers or engineers in ML infrastructure or foundational research.</li>\n</ul>\n<ul>\n<li>Deep technical expertise in representation learning, embedding models, or vector retrieval systems.</li>\n</ul>\n<ul>\n<li>Familiarity with transformer-based LLMs and how embedding spaces can interact with language model objectives.</li>\n</ul>\n<ul>\n<li>Research experience in areas such as contrastive learning, supervised or unsupervised embedding learning, or metric learning.</li>\n</ul>\n<ul>\n<li>A track record of building or scaling large machine learning systems, particularly embedding pipelines in production or research contexts.</li>\n</ul>\n<ul>\n<li>A first-principles mindset for challenging assumptions about how retrieval and memory should work for large models.</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_75ad55ca-61b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/020b2aae-8be0-408c-ab49-20eefa8541af","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$445K – $555K • Offers Equity","x-skills-required":["representation learning","embedding models","vector retrieval systems","transformer-based LLMs","contrastive learning","supervised or unsupervised embedding learning","metric learning"],"x-skills-preferred":["ML infrastructure","foundational research","large machine learning systems","embedding pipelines"],"datePosted":"2026-03-06T18:35:38.299Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"representation learning, embedding models, vector retrieval systems, transformer-based LLMs, contrastive learning, supervised or unsupervised embedding learning, metric learning, ML infrastructure, foundational research, large machine learning systems, embedding pipelines","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":445000,"maxValue":555000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_46bb9922-091"},"title":"ML Research Engineer - Hardware Codesign","description":"<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Department</strong></p>\n<p>Scaling</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$185K – $455K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong><strong>About the Team</strong></strong></p>\n<p>OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI.</p>\n<p><strong><strong>About the Role</strong></strong></p>\n<p>We’re seeking a Research-Hardware Codesign Engineer to operate at the boundary between model research and silicon/system architecture. You’ll help shape the numerics, architecture, and technology bets of future OpenAI silicon in collaboration with both Research and Hardware.</p>\n<p>Your work will include debugging gaps between rooflines and reality, writing quantization kernels, derisking numerics via model evals, quantifying system architecture tradeoffs, and implementing novel numeric RTL. This is a hands-on role for people who go looking for hard problems, get to ground truth, and drive it to production. Strong prioritization and clear, honest communication are essential.</p>\n<p>Location: San Francisco, CA (Hybrid: 3 days/week onsite)</p>\n<p>Relocation assistance available.</p>\n<p><strong><strong>In this role you will:</strong></strong></p>\n<ul>\n<li>Build on our roofline simulator to track evolving workloads, and deliver analyses that quantify the impact of system architecture decisions and support technology pathfinding.</li>\n</ul>\n<ul>\n<li>Debug gaps between performance simulation and real measurements; clearly communicate root cause, bottlenecks, and invalid assumptions.</li>\n</ul>\n<ul>\n<li>Write emulation kernels for low-precision numerics and lossy compression schemes, and get Research the information they need to trade efficiency with model quality.</li>\n</ul>\n<ul>\n<li>Prototype numerics modules by pushing RTL through synthesis; hand off novel numerics cleanly, or occasionally own an RTL module end-to-end.</li>\n</ul>\n<ul>\n<li>Proactively pull in new ML workloads, prototype them with rooflines and/or functional simulation, and drive initial evaluation of new opportunities or risks.</li>\n</ul>\n<ul>\n<li>Understand the whole picture from ML science to hardware optimization, and slice this end-to-end objective into near-term deliverables.</li>\n</ul>\n<ul>\n<li>Build ad-hoc collaborations across teams with very different goals and areas of expertise, and keep progress unblocked.</li>\n</ul>\n<ul>\n<li>Communicate design tradeoffs clearly with explicit assumptions and confidence levels; produce a trail of evidence that enables confident execution.</li>\n</ul>\n<p><strong><strong>You Will Thrive in this Role if:</strong></strong></p>\n<ul>\n<li>An exceptional track record of high-quality technical output, and a bias for shipping a prototype now and iterating later in the absence of clear requirements.</li>\n</ul>\n<ul>\n<li>Strong Python, and C++ or Rust, with a cautious attitude toward correctness and an intuition for clean extensibility.</li>\n</ul>\n<ul>\n<li>Experience writing Triton, CUDA, or similar, and an understanding of the resulting mapping of tensor ops to functional units.</li>\n</ul>\n<ul>\n<li>Working knowledge of PyTorch or JAX; experience in large ML codebases is a plus.</li>\n</ul>\n<ul>\n<li>Practical understanding of floating point numerics, the ML tradeoffs of reduced precision, and the current state of the art in model quantization.</li>\n</ul>\n<ul>\n<li>Deep understanding of transformer models, and strong intuition for transformer rooflines and the tradeoffs of sharded training and inference in large-scale ML systems.</li>\n</ul>\n<ul>\n<li>Experience writing RTL (especially for floating point logic) and understanding of PPA tradeoffs is a plus.</li>\n</ul>\n<ul>\n<li>Strong cross-functional communication (e.g. across ML researchers and hardware engineers); ability to slice ambiguous early-incubation ideas into concrete arenas in which progress can be made.</li>\n</ul>\n<p>_To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_46bb9922-091","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/5931abef-191b-417e-89f1-1d06f00e908c","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$185K – $455K","x-skills-required":["Python","C++","Rust","Triton","CUDA","PyTorch","JAX","Floating point numerics","Model quantization","Transformer models","RTL","PPA tradeoffs"],"x-skills-preferred":["Strong Python","C++ or Rust","Experience writing Triton","CUDA or similar","Working knowledge of PyTorch or JAX","Experience in large ML codebases"],"datePosted":"2026-03-06T18:28:06.437Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, C++, Rust, Triton, CUDA, PyTorch, JAX, Floating point numerics, Model quantization, Transformer models, RTL, PPA tradeoffs, Strong Python, C++ or Rust, Experience writing Triton, CUDA or similar, Working knowledge of PyTorch or JAX, Experience in large ML codebases","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":185000,"maxValue":455000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_0c077691-929"},"title":"Research Engineer / Machine Learning Engineer - B2B Applications","description":"<p><strong>Job Posting</strong></p>\n<p><strong>Research Engineer / Machine Learning Engineer - B2B Applications</strong></p>\n<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Location Type</strong></p>\n<p>Hybrid</p>\n<p><strong>Department</strong></p>\n<p>Applied AI</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$295K – $445K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong>About the Team</strong></p>\n<p>OpenAI is at the forefront of artificial intelligence, driving innovation and shaping the future with cutting-edge research. Our mission is to ensure that AI&#39;s benefits reach everyone. We are looking for visionary Research Engineers to join our Applied Voice Team, where you&#39;ll conduct groundbreaking research on speech models and transform it into real-world applications that can change industries, enhance human creativity, and solve complex problems.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Research Engineer in OpenAI&#39;s Applied Voice Team, you will have the opportunity to work with some of the brightest minds in AI. You&#39;ll design and build state-of-the-art speech models (speech-to-speech, transcribing, text to speech, etc.) and help turn research breakthroughs into tangible solutions in B2B applications, API and ChatGPT AVM. If you&#39;re excited about making AI technology accessible and impactful, this role is your chance to make a significant mark.</p>\n<p>In this role, you will:</p>\n<ul>\n<li>Innovate and Build: Design and build advanced machine learning models that solve real-world problems. Bring OpenAI&#39;s research from concept to implementation, creating AI-driven applications with a direct impact.</li>\n</ul>\n<ul>\n<li>Collaborate with the Best: Work closely with software engineers, product managers and forward deployed engineers to understand complex business challenges, address customer concerns and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives.</li>\n</ul>\n<ul>\n<li>Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches.</li>\n</ul>\n<ul>\n<li>Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices.</li>\n</ul>\n<ul>\n<li>Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large.</li>\n</ul>\n<p>You might thrive in this role if you:</p>\n<ul>\n<li>Master&#39;s/ PhD degree in Computer Science, Machine Learning, or a related field.</li>\n</ul>\n<ul>\n<li>2+ years of professional engineering experience (excluding internships) in relevant roles at tech and product-driven companies.</li>\n</ul>\n<ul>\n<li>Demonstrated experience in deep learning and transformers models</li>\n</ul>\n<ul>\n<li>Proficiency in frameworks like PyTorch or Tensorflow</li>\n</ul>\n<ul>\n<li>Strong foundation in data structures, algorithms, and software engineering principles.</li>\n</ul>\n<ul>\n<li>Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization</li>\n</ul>\n<ul>\n<li>Experience with speech models is a plus.</li>\n</ul>\n<ul>\n<li>Excellent problem-solving and analytical skills, with a proactive approach to challenges.</li>\n</ul>\n<ul>\n<li>Ability to work collaboratively with cross-functional teams.</li>\n</ul>\n<ul>\n<li>Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines</li>\n</ul>\n<ul>\n<li>Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you&#39;re missing to get the job done.</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_0c077691-929","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/46cd47bc-d4de-4826-aa2e-8b2e0da3c409","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$295K – $445K • Offers Equity","x-skills-required":["Master's/ PhD degree in Computer Science, Machine Learning, or a related field","2+ years of professional engineering experience (excluding internships) in relevant roles at tech and product-driven companies","Demonstrated experience in deep learning and transformers models","Proficiency in frameworks like PyTorch or Tensorflow","Strong foundation in data structures, algorithms, and software engineering principles"],"x-skills-preferred":["Experience with speech models","Excellent problem-solving and analytical skills, with a proactive approach to challenges","Ability to work collaboratively with cross-functional teams","Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines","Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done"],"datePosted":"2026-03-06T18:27:47.096Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Master's/ PhD degree in Computer Science, Machine Learning, or a related field, 2+ years of professional engineering experience (excluding internships) in relevant roles at tech and product-driven companies, Demonstrated experience in deep learning and transformers models, Proficiency in frameworks like PyTorch or Tensorflow, Strong foundation in data structures, algorithms, and software engineering principles, Experience with speech models, Excellent problem-solving and analytical skills, with a proactive approach to challenges, Ability to work collaboratively with cross-functional teams, Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines, Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":295000,"maxValue":445000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c6f7f50a-a66"},"title":"Research Engineer, Applied AI Engineering","description":"<p><strong>Research Engineer, Applied AI Engineering</strong></p>\n<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Department</strong></p>\n<p>Applied AI</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$250K – $555K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong>About the Team</strong></p>\n<p>OpenAI is at the forefront of artificial intelligence, driving innovation and shaping the future with cutting-edge research. Our mission is to ensure that AI&#39;s benefits reach everyone. We are looking for visionary Research Engineers to join our Applied Group, where you&#39;ll transform groundbreaking research into real-world applications that can change industries, enhance human creativity, and solve complex problems.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Research Engineer in OpenAI&#39;s Applied Group, you will have the opportunity to work with some of the brightest minds in AI. You&#39;ll contribute to deploying state-of-the-art models in production environments, helping turn research breakthroughs into tangible solutions. If you&#39;re excited about making AI technology accessible and impactful, this role is your chance to make a significant mark.</p>\n<p>In this role, you will:</p>\n<ul>\n<li>Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI&#39;s research from concept to implementation, creating AI-driven applications with a direct impact.</li>\n</ul>\n<ul>\n<li>Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives.</li>\n</ul>\n<ul>\n<li>Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches.</li>\n</ul>\n<ul>\n<li>Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices.</li>\n</ul>\n<ul>\n<li>Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large.</li>\n</ul>\n<p>You might thrive in this role if you:</p>\n<ul>\n<li>Master&#39;s/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field.</li>\n</ul>\n<ul>\n<li>Demonstrated experience in deep learning and transformers models</li>\n</ul>\n<ul>\n<li>Proficiency in frameworks like PyTorch or Tensorflow</li>\n</ul>\n<ul>\n<li>Strong foundation in data structures, algorithms, and software engineering principles.</li>\n</ul>\n<ul>\n<li>Experience with search relevance, ads ranking or LLMs is a plus.</li>\n</ul>\n<ul>\n<li>Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization</li>\n</ul>\n<ul>\n<li>Excellent problem-solving and analytical skills, with a proactive approach to challenges.</li>\n</ul>\n<ul>\n<li>Ability to work collaboratively with cross-functional teams.</li>\n</ul>\n<ul>\n<li>Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines</li>\n</ul>\n<ul>\n<li>Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you&#39;re missing to get the job done</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_c6f7f50a-a66","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/d44c9f70-4aef-45a4-a36a-54fb65663ccb","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$250K – $555K • Offers Equity","x-skills-required":["Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field","Demonstrated experience in deep learning and transformers models","Proficiency in frameworks like PyTorch or Tensorflow","Strong foundation in data structures, algorithms, and software engineering principles","Experience with search relevance, ads ranking or LLMs is a plus"],"x-skills-preferred":["Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization","Excellent problem-solving and analytical skills, with a proactive approach to challenges","Ability to work collaboratively with cross-functional teams","Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines","Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done"],"datePosted":"2026-03-06T18:26:13.276Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field, Demonstrated experience in deep learning and transformers models, Proficiency in frameworks like PyTorch or Tensorflow, Strong foundation in data structures, algorithms, and software engineering principles, Experience with search relevance, ads ranking or LLMs is a plus, Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization, Excellent problem-solving and analytical skills, with a proactive approach to challenges, Ability to work collaboratively with cross-functional teams, Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines, Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":250000,"maxValue":555000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_dd6e85f0-7a8"},"title":"Software Engineer, Monetization AI/ML","description":"<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Department</strong></p>\n<p>Applied AI</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$230K – $385K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong><strong>About the Team</strong></strong></p>\n<p>The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation.</p>\n<p>Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses.</p>\n<p>This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale.</p>\n<p><strong><strong>About the Role</strong></strong></p>\n<p>We’re looking for experienced Software Engineers to help build OpenAI’s foundational ads ranking and recommendation systems—the ML and AI platforms that determine how monetized experiences are selected, ordered, and optimized across OpenAI products.</p>\n<p>In this role, you’ll architect and implement large-scale, high-performance ML-driven systems with rigorous requirements around latency, correctness, safety, privacy, and continuous improvement. You’ll work on modern, transformer- and LLM-inspired architectures that move beyond traditional feature engineering toward more expressive, context-aware decisioning. Your work will have a direct revenue impact and make ChatGPT and other products accessible to more people with fewer usage limits or without having to pay.</p>\n<p>This is a deeply technical, 0→1 founding-stage role where you’ll operate across backend engineering, systems design, and applied AI/ML to help define the next generation of AI-native monetization and recommendation platforms.</p>\n<p>This role is exclusively based across our San Francisco and Seattle sites. We offer relocation assistance to new employees.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Architect, build, and evolve large-scale ads ranking and recommendation systems using modern ML and AI techniques</li>\n</ul>\n<ul>\n<li>Design and productionize LLM- and transformer-inspired models that leverage sequential signals, long-horizon context, and sparse or delayed feedback.</li>\n</ul>\n<ul>\n<li>Develop model-driven decision logic and inference pipelines that operate under real-world constraints around performance, reliability, and privacy.</li>\n</ul>\n<ul>\n<li>Partner closely with Product, Design, and Research to define requirements and translate ambiguous product goals into scalable ML systems.</li>\n</ul>\n<ul>\n<li>Prototype, experiment, and rapidly iterate on new model architectures and training approaches to improve relevance, quality, and efficiency.</li>\n</ul>\n<ul>\n<li>Build services and infrastructure that support training, evaluation, online inference, and continuous optimization of ML models.</li>\n</ul>\n<ul>\n<li>Establish strong measurement, experimentation, and debugging practices to understand model behavior and system-level outcomes.</li>\n</ul>\n<ul>\n<li>Contribute to technical strategy and help shape the long-term evolution of OpenAI’s monetization and recommendation stack.</li>\n</ul>\n<ul>\n<li>Embed safety, fairness, and policy considerations directly into model design and system architecture from first principles.</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Have 6+ years of experience building and scaling ML-powered systems in production environments.</li>\n</ul>\n<ul>\n<li>Have worked on ranking, recommendation, ads, marketplaces, or large-scale ML inference systems.</li>\n</ul>\n<ul>\n<li>Are comfortable operating across the full stack — from model development to backend services and production deployment.</li>\n</ul>\n<ul>\n<li>Enjoy deeply technical 0→1 problem spaces where architecture, strategy, and implementation overlap.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_dd6e85f0-7a8","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/a7b192bf-3d2e-4acb-9c97-fad3de0609db","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$230K – $385K","x-skills-required":["Software Engineer","Machine Learning","Artificial Intelligence","Full Stack Development","Backend Engineering","Systems Design","Applied AI/ML"],"x-skills-preferred":["Transformer- and LLM-inspired architectures","Sequential signals","Long-horizon context","Sparse or delayed feedback","Model-driven decision logic","Inference pipelines","Real-world constraints","Performance","Reliability","Privacy"],"datePosted":"2026-03-06T18:24:31.168Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Software Engineer, Machine Learning, Artificial Intelligence, Full Stack Development, Backend Engineering, Systems Design, Applied AI/ML, Transformer- and LLM-inspired architectures, Sequential signals, Long-horizon context, Sparse or delayed feedback, Model-driven decision logic, Inference pipelines, Real-world constraints, Performance, Reliability, Privacy","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":230000,"maxValue":385000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_1ee94df2-ca6"},"title":"Senior Research Engineer/Scientist - On-Device Transformer Models","description":"<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Location Type</strong></p>\n<p>Hybrid</p>\n<p><strong>Department</strong></p>\n<p>Consumer Products</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$380K – $445K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong>About the Team</strong></p>\n<p>The Future of Computing Research team is an Applied Research team within the Consumer Products group focused on developing new methods and models to support our vision for the future of computing as we advance forward in our mission of building AGI that benefits all of humanity.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Research Engineer/Scientist on the Future of Computing Research team, you will work together with _both_ the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities.</p>\n<p><strong>This role is based in San Francisco, CA. We follow a hybrid model with 4 days a week in the office and offer relocation assistance to new employees.</strong></p>\n<p><strong>In this role you will:</strong></p>\n<ul>\n<li>Train and evaluate multimodal SoTA models along axis that are important to our vision for future devices.</li>\n<li>Develop novel architectures that improve model performance when scaling the models themselves is not an option.</li>\n<li>Run through the necessary walls to take nascent research capabilities and turn them into capabilities we can build on top of.</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Have a research background related to developing on-device transformer models.</li>\n<li>Love performance optimization and working with GPU kernel engineers (but you do not need CUDA experience yourself).</li>\n<li>Do rigorous science (rather than vibes based). We need confidence in the experiments we run to move quickly.</li>\n<li>Have already spent time in the weeds teaching models to speak and perceive.</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_1ee94df2-ca6","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/7f9eb43b-423e-43e4-9f42-d14b8ba0f234","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$380K – $445K • Offers Equity","x-skills-required":["research background related to developing on-device transformer models","performance optimization","GPU kernel engineers","rigorous science","teaching models to speak and perceive"],"x-skills-preferred":["CUDA experience","multimodal SoTA models","novel architectures","nascent research capabilities"],"datePosted":"2026-03-06T18:22:44.309Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"research background related to developing on-device transformer models, performance optimization, GPU kernel engineers, rigorous science, teaching models to speak and perceive, CUDA experience, multimodal SoTA models, novel architectures, nascent research capabilities","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":380000,"maxValue":445000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_601ca6bf-9b1"},"title":"Senior Machine Learning Engineer, Natural Language Processing - PhD Early Career","description":"<p><strong>[2026] Senior Machine Learning Engineer, Natural Language Processing - PhD Early Career</strong></p>\n<p>San Mateo, CA, United States</p>\n<p>Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.</p>\n<p>At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device.</p>\n<p>A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.</p>\n<p>Natural Language Processing (NLP) is central to enabling massive-scale communication, creation, and safety across the Roblox platform. This role offers the unique opportunity to build and deploy cutting-edge <strong>NLP, speech, and generative AI models</strong> that operate at an unprecedented scale, impacting hundreds of millions of daily users.</p>\n<p>You will solve an extremely diverse range of high-scale language-related problems—from <strong>real-time moderation of voice and text</strong> to <strong>automatically localizing experiences</strong> and empowering users through <strong>LLM-driven creation tools</strong>. We combine cutting-edge research with large-scale engineering to bridge experimentation and production, designing algorithms that shape the next generation of language services for our immersive, user-generated content platform.</p>\n<p><strong><strong>Teams Hiring for This Role</strong></strong></p>\n<ul>\n<li><strong>Safety AI Systems:</strong>Dedicated to building end-to-end ML systems for maintaining civility and safety across the platform, operating at massive scale. This includes:</li>\n</ul>\n<ul>\n<li><strong>Real-time Moderation:</strong> Building world-class NLP and speech models for <strong>real-time moderation of voice and text</strong> (processing over 6 billion messages daily) and advanced interventions that measurably improve user civility.</li>\n</ul>\n<ul>\n<li><strong>Critical Harms &amp; Advanced Detection:</strong> Developing specialized LLM agents, behavioral analysis, and graph systems for detecting and preventing rare, high-risk scenarios (e.g., child safety, terrorism), requiring adversarial thinking and multi-step reasoning.</li>\n</ul>\n<ul>\n<li><strong>Safety Data Quality:</strong> Ensuring all Safety AI systems are robust by managing the core data infrastructure, MLOps, and Active Learning initiatives for continuous model improvement.</li>\n</ul>\n<p><strong>You Will</strong></p>\n<ul>\n<li>Design and implement <strong>deep learning-based NLP and speech solutions</strong> that address problems across Roblox, from creation to safety.</li>\n</ul>\n<ul>\n<li>Develop advanced models, including <strong>Large Language Models (LLMs), machine translation, and generative AI</strong>, for user interactions, content creation, and moderation.</li>\n</ul>\n<ul>\n<li>Have the independence and <strong>end-to-end responsibility</strong> to develop NLP/ML-based services that are scalable and resilient.</li>\n</ul>\n<ul>\n<li>Be a <strong>technical bar-raiser</strong> for cutting-edge ML technology, high code quality, and architectural designs.</li>\n</ul>\n<ul>\n<li>Work backward from user and product needs to deliver ML solutions that drive engagement, safety, and ecosystem growth.</li>\n</ul>\n<p><strong>You Have</strong></p>\n<ul>\n<li>Possessing or pursuing a Ph.D. in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field, with a thesis aligned to Roblox’s research areas.</li>\n</ul>\n<ul>\n<li>Expertise in one or more areas: NLP, Speech Models, Large Language Models, Machine Translation, or Generative AI (including diffusion models).</li>\n</ul>\n<ul>\n<li>Experience with transformer-based model design, training, serving, and product integration.</li>\n</ul>\n<ul>\n<li>A strong research track record, evidenced by multiple publications and presentations in top-tier, peer-reviewed venues (e.g., ACL, EMNLP, Interspeech, ICML, NeurIPS).</li>\n</ul>\n<ul>\n<li>Proficiency in one or more programming languages (e.g., Python, C++, Go, Java) and experience building and optimizing large-scale systems.</li>\n</ul>\n<p>You may redact age, date of birth, and dates of attendance/graduation from your resume if you prefer.</p>\n<p>As you apply, you can find more information about our process by signing up for Speak\\_. You&#39;ll gain access to our practice assessment, comprehensive guides, FAQs, and modules designed to help you ace the hiring process.</p>\n<p>For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on <strong>this page</strong>.</p>\n<p>Annual Salary Range</p>\n<p>$195,780—$242,100 USD</p>\n<p>Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_601ca6bf-9b1","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Roblox","sameAs":"https://careers.roblox.com","logo":"https://logos.yubhub.co/careers.roblox.com.png"},"x-apply-url":"https://careers.roblox.com/jobs/7324377","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$195,780—$242,100 USD","x-skills-required":["NLP","Speech Models","Large Language Models","Machine Translation","Generative AI","Python","C++","Go","Java","Transformer-based model design","Training","Serving","Product integration"],"x-skills-preferred":["Deep learning","Computer vision","Natural language processing","Speech recognition","Text analysis","Sentiment analysis","Named entity recognition","Part-of-speech tagging","Dependency parsing","Semantic role labeling"],"datePosted":"2026-03-06T14:18:50.958Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Mateo, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"NLP, Speech Models, Large Language Models, Machine Translation, Generative AI, Python, C++, Go, Java, Transformer-based model design, Training, Serving, Product integration, Deep learning, Computer vision, Natural language processing, Speech recognition, Text analysis, Sentiment analysis, Named entity recognition, Part-of-speech tagging, Dependency parsing, Semantic role labeling","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":195780,"maxValue":242100,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d8710a49-05d"},"title":"Principal Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Principal Applied Scientist at their New York office. This role sits at the heart of advanced AI at web scale, shaping the future of key systems within Microsoft Ads, Copilot, and beyond. You&#39;ll work directly with leadership to deliver scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>About the Role</strong></p>\n<p>In this role, the Principal Applied Scientist will design and implement state-of-the-art machine learning models and algorithms that power key systems within Microsoft Ads, Copilot, and beyond. The work will directly impact millions of users and advertisers by delivering scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.</li>\n<li>Design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation and ad relevance.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Proven experience in programming and data analysis skills.</li>\n<li>Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, transformers or LLM.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>6+ years of experience in developing and deploying large-scale machine learning models.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary</li>\n<li>Comprehensive benefits package</li>\n<li>Opportunities for professional growth and development</li>\n<li>Collaborative and dynamic work environment</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_d8710a49-05d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/principal-applied-scientist-17/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$139,900 – $274,800 per year","x-skills-required":["machine learning","statistics","econometrics","computer science","electrical or computer engineering"],"x-skills-preferred":["generative AI","deep learning","reinforcement learning","transformers","LLM"],"datePosted":"2026-03-06T07:33:03.226Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, statistics, econometrics, computer science, electrical or computer engineering, generative AI, deep learning, reinforcement learning, transformers, LLM","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":139900,"maxValue":274800,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_066d45bf-f6e"},"title":"Principal Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Principal Applied Scientist at their Mountain View office. This role sits at the heart of advanced AI at web scale, shaping the future of key systems within Microsoft Ads, Copilot, and beyond. You&#39;ll work directly with leadership to deliver scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>About the Role</strong></p>\n<p>In this role, the Principal Applied Scientist will design and implement state-of-the-art machine learning models and algorithms that power key systems within Microsoft Ads, Copilot, and beyond. The work will directly impact millions of users and advertisers by delivering scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.</li>\n<li>Design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation and ad relevance.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Proven experience in programming and data analysis skills.</li>\n<li>Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, transformers or LLM.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Proven experience in developing and deploying large-scale machine learning models.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary</li>\n<li>Comprehensive benefits package</li>\n<li>Opportunities for professional growth and development</li>\n<li>Collaborative and dynamic work environment</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_066d45bf-f6e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/principal-applied-scientist-16/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$139,900 – $274,800 per year","x-skills-required":["machine learning","statistics","econometrics","computer science","electrical or computer engineering"],"x-skills-preferred":["generative AI","deep learning","reinforcement learning","transformers","LLM"],"datePosted":"2026-03-06T07:32:49.983Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, statistics, econometrics, computer science, electrical or computer engineering, generative AI, deep learning, reinforcement learning, transformers, LLM","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":139900,"maxValue":274800,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_9c3ddd52-017"},"title":"Principal Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Principal Applied Scientist at their Redmond office. This role sits at the heart of advanced AI at web scale, shaping the future of key systems within Microsoft Ads, Copilot, and beyond. You&#39;ll design and implement state-of-the-art machine learning models and algorithms that power scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>About the Role</strong></p>\n<p>In this role, you will develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot. You will design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation and ad relevance. You will drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions. You will build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications. You will stay at the forefront of AI research, incorporating the latest advancements to drive innovation and impact across Microsoft platforms.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.</li>\n<li>Design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation and ad relevance.</li>\n<li>Drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions.</li>\n<li>Build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Proven experience in programming and data analysis skills.</li>\n<li>Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, transformers or LLM.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Strong problem-solving skills and ability to work independently.</li>\n<li>Excellent communication and collaboration skills.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary.</li>\n<li>Comprehensive benefits package.</li>\n<li>Opportunities for professional growth and development.</li>\n<li>Collaborative and dynamic work environment.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_9c3ddd52-017","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/principal-applied-scientist-15/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$139,900 - $274,800 per year","x-skills-required":["machine learning","deep learning","reinforcement learning","transformers","LLM","programming","data analysis"],"x-skills-preferred":["Generative AI","A/B testing","offline validation","data pipelines","frameworks"],"datePosted":"2026-03-06T07:31:51.153Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, deep learning, reinforcement learning, transformers, LLM, programming, data analysis, Generative AI, A/B testing, offline validation, data pipelines, frameworks","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":139900,"maxValue":274800,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6cedf31a-a76"},"title":"Senior Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft are looking for a talented Senior Applied Scientist at their Mountain View office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising artificial intelligence technology. You&#39;ll work directly with leadership to shape the company&#39;s direction in the technology market.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Senior Applied Scientist, you will design and implement cutting-edge machine learning models and algorithms that power relevance systems across all surfaces for Microsoft Ads and Shopping including Bing, Copilot, and beyond. You will have a direct impact on millions of users and advertisers, delivering scalable solutions to enhance ad relevance and optimize user experiences.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Own high-impact and open-ended relevance problem areas across Product Ads and Shopping including providing strategic direction to solve problems and applying deep subject matter knowledge to support business impact.</li>\n<li>Drive algorithmic and modeling improvements to the system using primarily deep learning techniques from NLP and computer vision, including latest LLM models, to deliver clear and measurable product impact.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor&#39;s Degree in Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master&#39;s Degree in Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n<li>4+ years working experience in statistical natural language processing (NLP) with the latest deep learning technologies including transformer and LLMs OR 4+ years working experience in Computer Vision (CV) with latest deep learning technologies including Vision Transformers.</li>\n<li>4+ years working experience with coding in production systems using C++, C#, Java or Python.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Strong technical judgment on metrics, evaluation strategies, and tradeoffs optimizing for overall product ROI rather than isolated metrics.</li>\n<li>Ability to operate with high independence and accountability, anticipating risks, planning for unknowns, and requiring minimal oversight to deliver sustained impact at scale.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary</li>\n<li>Comprehensive benefits package</li>\n<li>Opportunities for professional growth and development</li>\n<li>Collaborative and dynamic work environment</li>\n<li>Recognition and rewards for outstanding performance</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_6cedf31a-a76","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-33/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$119,800 - $234,700 per year","x-skills-required":["Data Science","Machine Learning","Statistics","Computer Science","Computer Engineering","NLP","Computer Vision","C++","C#","Java","Python"],"x-skills-preferred":["Transformer","LLMs","Vision Transformers"],"datePosted":"2026-03-06T07:31:07.758Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Data Science, Machine Learning, Statistics, Computer Science, Computer Engineering, NLP, Computer Vision, C++, C#, Java, Python, Transformer, LLMs, Vision Transformers","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":119800,"maxValue":234700,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_cfee4a87-9c7"},"title":"Member of Technical Staff, Multimodal Infrastructure","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Member of Technical Staff, Multimodal Infrastructure to help build the next wave of capabilities of our personalized AI assistant, Copilot. We&#39;re looking for someone who will bring an abundance of positive energy, empathy, and kindness to the team every day, in addition to being highly effective.</p>\n<p><strong>About the Role</strong></p>\n<p>We&#39;re looking for someone who will design, develop and maintain large-scale multimodal data processing pipelines, model pretraining and post-training frameworks, and model inference and serving frameworks. You will work closely with research scientists and product engineers on multimodal data processing, model training, inference and serving tasks. As a contributing member of the core group of engineers, you would also bring to the table best practices driving architectural changes and influence roadmap of relevant software and hardware components.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Design, develop and maintain large-scale multimodal data processing pipelines.</li>\n<li>Design, develop and maintain large-scale multimodal model pretraining and post-training frameworks.</li>\n<li>Design, develop and maintain large-scale multimodal model inference and serving frameworks.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor&#39;s Degree in Computer Science, or related technical discipline AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Strong proficiency in distributed data processing infra (resource utilization management, fault tolerance, ray &amp; spark) and CPU/GPU batch processing optimizations.</li>\n<li>Experience with state-of-art model inference and serving frameworks.</li>\n<li>Experience with image/video/audio data processing.</li>\n<li>Experience with common data formats for efficient I/O.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Enjoy working in a fast-paced, design-driven, product development cycle.</li>\n<li>Embody our Culture and Values.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location.</li>\n<li>Comprehensive health and wellbeing benefits.</li>\n<li>Professional development opportunities.</li>\n<li>Financial benefits (bonus, equity, pension, etc.).</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_cfee4a87-9c7","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/member-of-technical-staff-multimodal-infrastructure-mai-superintelligence-team-2/","x-work-arrangement":"hybrid","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["C","C++","C#","Java","JavaScript","Python","Distributed data processing infra","CPU/GPU batch processing optimizations","State-of-art model inference and serving frameworks","Image/video/audio data processing","Common data formats for efficient I/O"],"x-skills-preferred":["Deep learning frameworks","Auto-regressive and diffusion transformer models","Distributed training techniques","Image/video generation and editing","Efficient architectures","Efficient model design","Reinforcement learning training methods"],"datePosted":"2026-03-06T07:31:05.608Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"C, C++, C#, Java, JavaScript, Python, Distributed data processing infra, CPU/GPU batch processing optimizations, State-of-art model inference and serving frameworks, Image/video/audio data processing, Common data formats for efficient I/O, Deep learning frameworks, Auto-regressive and diffusion transformer models, Distributed training techniques, Image/video generation and editing, Efficient architectures, Efficient model design, Reinforcement learning training methods"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_a74a8be0-e9d"},"title":"Senior Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Senior Applied Scientist at their Redmond office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising artificial intelligence technology. You&#39;ll work directly with leadership to shape the company&#39;s direction in the AI and machine learning markets.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Senior Applied Scientist, you will design and implement cutting-edge machine learning models and algorithms that power relevance systems across all surfaces for Microsoft Ads and Shopping including Bing, Copilot, and beyond. You will have a direct impact on millions of users and advertisers, delivering scalable solutions to enhance ad relevance and optimize user experiences. This role is part of Microsoft Artificial Intelligence (MAI)-Ads Engineering and is responsible for the end-to-end relevance problem for our ads and shopping products.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Own high-impact and open-ended relevance problem areas across Product Ads and Shopping including providing strategic direction to solve problems and applying deep subject matter knowledge to support business impact.</li>\n<li>Drive algorithmic and modeling improvements to the system using primarily deep learning techniques from NLP and computer vision, including latest LLM models, to deliver clear and measurable product impact.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor&#39;s Degree in Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master&#39;s Degree in Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n<li>4+ years working experience in statistical natural language processing (NLP) with the latest deep learning technologies including transformer and LLMs OR 4+ years working experience in Computer Vision (CV) with latest deep learning technologies including Vision Transformers.</li>\n<li>4+ years working experience with coding in production systems using C++, C#, Java or Python.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Strong technical judgment and problem-solving skills.</li>\n<li>Excellent communication and collaboration skills.</li>\n<li>Ability to work independently and as part of a team.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary range: $119,800 - $234,700 per year.</li>\n<li>Comprehensive benefits package, including medical, dental, and vision insurance.</li>\n<li>401(k) matching program.</li>\n<li>Paid time off and holidays.</li>\n<li>Opportunities for professional growth and development.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_a74a8be0-e9d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-32/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$119,800 - $234,700 per year","x-skills-required":["Data Science","Machine Learning","Statistics","Computer Science","Computer Engineering","NLP","CV","C++","C#","Java","Python"],"x-skills-preferred":["Transformer","LLMs","Vision Transformers"],"datePosted":"2026-03-06T07:30:32.355Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Data Science, Machine Learning, Statistics, Computer Science, Computer Engineering, NLP, CV, C++, C#, Java, Python, Transformer, LLMs, Vision Transformers","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":119800,"maxValue":234700,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_a82f064b-623"},"title":"Member of Technical Staff, Multimodal Infrastructure","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Member of Technical Staff, Multimodal Infrastructure to help build the next wave of capabilities of our personalized AI assistant, Copilot. We’re looking for someone who will bring an abundance of positive energy, empathy, and kindness to the team every day, in addition to being highly effective.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Member of Technical Staff, Multimodal Infrastructure, you will be responsible for designing, developing, and maintaining large-scale multimodal data processing pipelines, model pretraining and post-training frameworks, and model inference and serving frameworks. You will work closely with research scientists and product engineers to solve infra-related problems and find a path to get things done despite roadblocks to get your work into the hands of users quickly and iteratively.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Design, develop, and maintain large-scale multimodal data processing pipelines.</li>\n<li>Design, develop, and maintain large-scale multimodal model pretraining and post-training frameworks.</li>\n<li>Design, develop, and maintain large-scale multimodal model inference and serving frameworks.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Computer Science, or related technical discipline AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Strong proficiency in distributed data processing infra (resource utilization management, fault tolerance, ray &amp; spark) and CPU/GPU batch processing optimizations.</li>\n<li>Experience with state-of-art model inference and serving frameworks.</li>\n<li>Experience with image/video/audio data processing.</li>\n<li>Experience with common data formats for efficient I/O.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Enjoy working in a fast-paced, design-driven, product development cycle.</li>\n<li>Embody our Culture and Values.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location.</li>\n<li>Comprehensive health and wellbeing benefits.</li>\n<li>Professional development opportunities.</li>\n<li>Financial benefits (bonus, equity, pension, etc.).</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_a82f064b-623","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/member-of-technical-staff-multimodal-infrastructure-mai-superintelligence-team/","x-work-arrangement":"hybrid","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["C","C++","C#","Java","JavaScript","Python","Distributed data processing infra","CPU/GPU batch processing optimizations","State-of-art model inference and serving frameworks","Image/video/audio data processing","Common data formats for efficient I/O"],"x-skills-preferred":["Auto-regressive and diffusion transformer models","Distributed training techniques","Image/video generation and editing","Efficient architectures","Efficient model design","Reinforcement learning training methods"],"datePosted":"2026-03-06T07:30:19.312Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"C, C++, C#, Java, JavaScript, Python, Distributed data processing infra, CPU/GPU batch processing optimizations, State-of-art model inference and serving frameworks, Image/video/audio data processing, Common data formats for efficient I/O, Auto-regressive and diffusion transformer models, Distributed training techniques, Image/video generation and editing, Efficient architectures, Efficient model design, Reinforcement learning training methods"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_ccb8c130-7e6"},"title":"Senior Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft are looking for a talented Senior Applied Scientist at their Redmond office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising the advertising technology space. You&#39;ll work directly with leadership to shape the company&#39;s direction in the online advertising market.</p>\n<p><strong>About the Role</strong></p>\n<p>In this role, the Senior Applied Scientist will design and implement state-of-the-art machine learning models and algorithms that power key systems within Microsoft Ads, Microsoft Audience Network, Copilot, and beyond. Your work will directly impact millions of users and advertisers by delivering scalable solutions that enhance ad relevance and optimize user experiences.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.</li>\n<li>Design scalable algorithms for online and offline systems, delivering innovative solutions for content selection, user engagement modeling, and ad generation.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Proven experience in programming and data analysis skills 2+ years of experience in developing and deploying large-scale machine learning models.</li>\n<li>Proven expertise in the areas of Generative AI, deep learning, or transformers.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_ccb8c130-7e6","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-36/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"USD $119,800 – $234,700 per year","x-skills-required":["machine learning","statistics","econometrics","computer science","electrical or computer engineering"],"x-skills-preferred":["generative AI","deep learning","transformers"],"datePosted":"2026-03-06T07:29:09.728Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, statistics, econometrics, computer science, electrical or computer engineering, generative AI, deep learning, transformers","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":119800,"maxValue":234700,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_377390f9-35b"},"title":"Senior Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft are looking for a talented Senior Applied Scientist at their Mountain View office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising the advertising space. You&#39;ll work directly with leadership to shape the company&#39;s direction in the online advertising market.</p>\n<p><strong>About the Role</strong></p>\n<p>In this role, the Senior Applied Scientist will design and implement state-of-the-art machine learning models and algorithms that power key systems within Microsoft Ads, Microsoft Audience Network, Copilot, and beyond. Your work will directly impact millions of users and advertisers by delivering scalable solutions that enhance ad relevance and optimize user experiences.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.</li>\n<li>Design scalable algorithms for online and offline systems, delivering innovative solutions for content selection, user engagement modeling, and ad generation.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Proven experience in programming and data analysis skills 2+ years of experience in developing and deploying large-scale machine learning models.</li>\n<li>Proven expertise in the areas of Generative AI, deep learning, or transformers.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_377390f9-35b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-35/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"USD $119,800 – $234,700 per year","x-skills-required":["machine learning","statistics","econometrics","computer science","electrical or computer engineering"],"x-skills-preferred":["generative AI","deep learning","transformers"],"datePosted":"2026-03-06T07:29:00.639Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, statistics, econometrics, computer science, electrical or computer engineering, generative AI, deep learning, transformers","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":119800,"maxValue":234700,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_357f2743-062"},"title":"Senior Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Senior Applied Scientist at their Mountain View office. This role sits at the heart of advanced AI at web scale, shaping the future of key systems within Microsoft Ads, Copilot, and beyond. You&#39;ll design and implement state-of-the-art machine learning models and algorithms that power scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>About the Role</strong></p>\n<p>In this role, you will develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot. You will design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation, and ad relevance. You will drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions. You will build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications. You will stay at the forefront of AI research, incorporating the latest advancements to drive innovation and impact across Microsoft platforms.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.</li>\n<li>Design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation, and ad relevance.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Proven experience in programming and data analysis skills.</li>\n<li>Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, transformers or LLM.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Strong communication and collaboration skills.</li>\n<li>Ability to work in a fast-paced environment and adapt to changing priorities.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary range of $119,800 - $234,700 per year.</li>\n<li>Comprehensive benefits package, including medical, dental, and vision insurance.</li>\n<li>401(k) matching program.</li>\n<li>Paid time off and holidays.</li>\n<li>Opportunities for professional growth and development.</li>\n<li>Collaborative and dynamic work environment.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_357f2743-062","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-19/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$119,800 - $234,700 per year","x-skills-required":["machine learning","artificial intelligence","programming","data analysis","statistics","econometrics","computer science","electrical engineering"],"x-skills-preferred":["generative AI","deep learning","reinforcement learning","transformers","LLM"],"datePosted":"2026-03-06T07:28:23.814Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, artificial intelligence, programming, data analysis, statistics, econometrics, computer science, electrical engineering, generative AI, deep learning, reinforcement learning, transformers, LLM","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":119800,"maxValue":234700,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_15581007-5d0"},"title":"Senior Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Senior Applied Scientist at their Vancouver office. This role sits at the heart of advanced AI at web scale, shaping the future of key systems within Microsoft Ads, Copilot, and beyond. You&#39;ll design and implement state-of-the-art machine learning models and algorithms that power scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Senior Applied Scientist, you will be responsible for developing and deploying cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning. You will design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation, and ad relevance. You will drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions. You will build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications. You will stay at the forefront of AI research, incorporating the latest advancements to drive innovation and impact across Microsoft platforms.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.</li>\n<li>Design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation, and ad relevance.</li>\n<li>Drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions.</li>\n<li>Build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>4+ years of experience in statistics, predictive analytics, research, or a related field.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, transformers, or LLM.</li>\n<li>5+ years of experience in developing and deploying large-scale machine learning models.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Strong problem-solving skills and ability to work independently.</li>\n<li>Excellent communication and collaboration skills.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary range: CAD $114,400 - CAD $203,900 per year.</li>\n<li>Comprehensive benefits package, including health, dental, and vision insurance.</li>\n<li>Opportunities for professional growth and development.</li>\n<li>Collaborative and dynamic work environment.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_15581007-5d0","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-16/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"CAD $114,400 - CAD $203,900 per year","x-skills-required":["machine learning","deep learning","reinforcement learning","transformers","LLM"],"x-skills-preferred":["Generative AI","data pipelines","frameworks"],"datePosted":"2026-03-06T07:27:20.074Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Vancouver"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, deep learning, reinforcement learning, transformers, LLM, Generative AI, data pipelines, frameworks","baseSalary":{"@type":"MonetaryAmount","currency":"CAD","value":{"@type":"QuantitativeValue","minValue":114400,"maxValue":203900,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2ee60f78-c8d"},"title":"Applied Scientist II","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Applied Scientist II at their Redmond office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising AI technology. You&#39;ll work directly with leadership to shape the company&#39;s direction in the AI market.</p>\n<p><strong>About the Role</strong></p>\n<p>As an Applied Scientist II, you will be responsible for building and maintaining production machine learning models to generate image and text assets, multimodal representation and predict ad quality. You will find insights and form hypothesis on web-scale data with various machine learning, computer vision, feature engineering, statistical, and data mining techniques. You will design experiments, understand the resulting data, and produce actionable, trustworthy conclusions from them. You will craft and optimize prompts for effective LLM and VLM performance, and wrangle large amounts of data using various tools.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Building and maintaining production machine learning models to generate image and text assets, multimodal representation and predict ad quality.</li>\n<li>Finding insights and forming hypothesis on web-scale data with various machine learning, computer vision, feature engineering, statistical, and data mining techniques.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor&#39;s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research) OR Master&#39;s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Experience with Large Language Models: Demonstrated experience working with LLMs/VLMs, such as GPT, BERT, or similar models, including knowledge of their strengths, limitations, and capabilities.</li>\n<li>Solid Understanding of NLP and CV: In-depth knowledge of natural language processing (NLP) and computer vision techniques and concepts, including tokenization, semantic analysis, and text generation, multimodal representation, etc.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Experience delivering, scaling, and maintaining highly successful and innovative machine learning products with your fingerprints all over them.</li>\n<li>Experience in parallel or distributed processing, high performance computing, stream computing and SCOPE.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary and benefits package.</li>\n<li>Opportunities for professional growth and development.</li>\n<li>Collaborative and dynamic work environment.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_2ee60f78-c8d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/applied-scientist-ii-2/","x-work-arrangement":"onsite","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"Competitive salary and benefits package.","x-skills-required":["Machine Learning","Computer Vision","NLP","Python","R","C++","Java","SQL"],"x-skills-preferred":["Large Language Models","Deep Learning","Transformers","Attention","CNN","RNN"],"datePosted":"2026-03-06T07:26:50.941Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, Computer Vision, NLP, Python, R, C++, Java, SQL, Large Language Models, Deep Learning, Transformers, Attention, CNN, RNN"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_05ddca1c-456"},"title":"Senior Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Senior Applied Scientist at their Toronto office. This role sits at the heart of advanced AI at web scale, shaping the future of key systems within Microsoft Ads, Copilot, and beyond. The work will directly impact millions of users and advertisers by delivering scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>About the Role</strong></p>\n<p>In this role, the Senior Applied Scientist will design and implement state-of-the-art machine learning models and algorithms that power key systems within Microsoft Ads, Copilot, and beyond. The work will directly impact millions of users and advertisers by delivering scalable solutions that enhance ad relevance and optimize user and advertiser experiences. Responsibilities span the full modeling lifecycle, including training data and labeling strategy, feature and signal design, model development, and rigorous offline and online evaluation. Engineers and applied scientists work closely at the intersection of machine learning, economics, and large-scale systems to deliver high-performance real-time inference and robust experimentation in production.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.</li>\n<li>Design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation and ad relevance.</li>\n<li>Drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions.</li>\n<li>Build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications.</li>\n<li>Stay at the forefront of AI research, incorporating the latest advancements to drive innovation and impact across Microsoft platforms.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Proven experience in programming and data analysis skills.</li>\n<li>Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, transformers or LLM.</li>\n<li>5+ years of experience in developing and deploying large-scale machine learning models.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Strong problem-solving skills and ability to work independently.</li>\n<li>Excellent communication and collaboration skills.</li>\n<li>Ability to work in a fast-paced environment and adapt to changing priorities.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary range of CAD $114,400 – CAD $203,900 per year.</li>\n<li>Comprehensive benefits package, including health, dental, and vision insurance.</li>\n<li>Opportunities for professional development and growth within the company.</li>\n<li>Collaborative and dynamic work environment.</li>\n<li>Access to cutting-edge technology and resources.</li>\n<li>Flexible work arrangements, including remote work options.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_05ddca1c-456","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-17/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"CAD $114,400 – CAD $203,900 per year","x-skills-required":["machine learning","statistics","econometrics","computer science","electrical or computer engineering","programming","data analysis","generative AI","deep learning","reinforcement learning","transformers","LLM"],"x-skills-preferred":["problem-solving","communication","collaboration","adaptability"],"datePosted":"2026-03-05T19:50:12.889Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Toronto"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, statistics, econometrics, computer science, electrical or computer engineering, programming, data analysis, generative AI, deep learning, reinforcement learning, transformers, LLM, problem-solving, communication, collaboration, adaptability","baseSalary":{"@type":"MonetaryAmount","currency":"CAD","value":{"@type":"QuantitativeValue","minValue":114400,"maxValue":203900,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_9b2262ac-604"},"title":"Senior Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Senior Applied Scientist at their Redmond office. This role sits at the heart of advanced AI at web scale, shaping the future of key systems within Microsoft Ads, Copilot, and beyond. You&#39;ll design and implement state-of-the-art machine learning models and algorithms that power scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>About the Role</strong></p>\n<p>In this role, you will develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot. You will design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation, and ad relevance. You will drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions. You will build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications. You will stay at the forefront of AI research, incorporating the latest advancements to drive innovation and impact across Microsoft platforms.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.</li>\n<li>Design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation, and ad relevance.</li>\n<li>Drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions.</li>\n<li>Build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Proven experience in programming and data analysis skills.</li>\n<li>Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, transformers or LLM.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Strong problem-solving skills and ability to work independently.</li>\n<li>Excellent communication and collaboration skills.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary presumption of $119,800 - $234,700 per year.</li>\n<li>Comprehensive benefits package, including medical, dental, and vision insurance.</li>\n<li>401(k) matching program.</li>\n<li>Paid time off and holidays.</li>\n<li>Opportunities for professional growth and development.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_9b2262ac-604","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-18/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$119,800 - $234,700 per year","x-skills-required":["machine learning","artificial intelligence","data analysis","programming","statistics","econometrics","computer science","electrical engineering"],"x-skills-preferred":["generative AI","deep learning","reinforcement learning","transformers","LLM"],"datePosted":"2026-03-05T19:46:18.960Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, artificial intelligence, data analysis, programming, statistics, econometrics, computer science, electrical engineering, generative AI, deep learning, reinforcement learning, transformers, LLM","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":119800,"maxValue":234700,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2f5d701f-41d"},"title":"Research Engineering Manager - Model Training","description":"<p>We are seeking a Research Engineering Manager to lead the team of all-star AI researchers and engineers responsible for developing the models that drive our products. Our team has developed some of the most advanced models for agentic research, query understanding, and other domains that require accuracy and depth. As we expand our userbase and portfolio of product surfaces, our in-house models are increasingly critical to providing a premium, high-taste experience for the world’s most sophisticated users.</p>\n<p><strong>What you&#39;ll do</strong></p>\n<p>You will dive into our rich datasets of conversational and agentic queries, leveraging cutting-edge training techniques to scale AI model performance. Through hands-on technical and organizational leadership, you will empower your team to develop SotA models for the use cases that matter most to our business and our users.</p>\n<ul>\n<li>Lead a team of researchers and engineers focused on training SotA models for Perplexity-relevant use cases, leveraging the latest supervised and reinforcement learning techniques.</li>\n<li>Drive research and engineering efforts to develop production models through advanced model training and alignment techniques, including RL, SFT, and other approaches.</li>\n<li>Become deeply familiar with the team’s technical stack, leading from the front through hands-on technical contributions.</li>\n<li>Own the data, training, and eval pipelines required to train and continuously improve LLM models.</li>\n<li>Design and iterate on model training and finetuning algorithms (e.g., preference-based methods, reinforcement learning from human or AI feedback) through an approach that balances scientific rigor and iteration velocity.</li>\n<li>Design evaluations and improve the production model training pipeline to reliably deliver models that lie on the Pareto frontier of speed and quality.</li>\n<li>Work closely with engineering teams to integrate in-house models into our product and rapidly iterate based on real-world usage.</li>\n<li>Manage day-to-day execution, project planning, and prioritization for the model training team to hit ambitious quality and performance goals.</li>\n</ul>\n<p><strong>What you need</strong></p>\n<ul>\n<li>Proven experience with large-scale LLMs and Deep Learning systems.</li>\n<li>Strong Python and PyTorch skills; versatility across languages and frameworks is a plus.</li>\n<li>Experience leading or managing research or engineering teams working on large-scale AI model development, including driving complex projects from idea to production.</li>\n<li>Self-starter with a willingness to take ownership of tasks and navigate ambiguity in a fast-moving environment.</li>\n<li>Passion for tackling challenging problems in AI model quality, speed, safety, and reliability.</li>\n<li>10+ years of technical experience, with at least 2 of those years as a manager and at least 4 of those years working on large-scale AI model development.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_2f5d701f-41d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Perplexity","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/perplexity.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/perplexity/08d510a4-c217-4967-a035-b5b8147e5c62","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$300K - $485K","x-skills-required":["large-scale LLMs","Deep Learning systems","Python","PyTorch","experience leading or managing research or engineering teams","self-starter"],"x-skills-preferred":["PhD in Machine Learning or related areas","experience training very large Transformer-based models","prior experience designing evaluations and production training pipelines"],"datePosted":"2026-03-04T12:25:52.038Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"large-scale LLMs, Deep Learning systems, Python, PyTorch, experience leading or managing research or engineering teams, self-starter, PhD in Machine Learning or related areas, experience training very large Transformer-based models, prior experience designing evaluations and production training pipelines","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":300000,"maxValue":485000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_fa7fcb6f-abe"},"title":"Senior Data Scientist","description":"<p>Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.</p>\n<p><strong>What you&#39;ll do</strong></p>\n<p>This Senior Data Scientist role will focus on designing and developing advanced AI-driven solutions for game developers and gamers. The ideal candidate will have strong expertise in Reinforcement Learning (RL), Generative AI agents, and Retrieval-Augmented Generation (RAG) to create intelligent gaming tools and experiences.</p>\n<ul>\n<li>Research, design, and implement rewards-based agents using Reinforcement Learning (RL) for testing gaming applications.</li>\n<li>Develop and optimize agents and advanced RAG-based solutions for dynamic game content creation, adaptive player interactions, and enhanced gaming experiences.</li>\n</ul>\n<p><strong>What you need</strong></p>\n<ul>\n<li>Strong background in Reinforcement Learning (RL), Generative AI agents, and RAG (Retrieval-Augmented Generation).</li>\n<li>Proficiency in Python and experience with PyTorch or TensorFlow for deep learning.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_fa7fcb6f-abe","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Razer","sameAs":"https://razer.wd3.myworkdayjobs.com","logo":"https://logos.yubhub.co/razer.com.png"},"x-apply-url":"https://razer.wd3.myworkdayjobs.com/en-US/Careers/job/Singapore/AI-Data-Scientist_JR2025005484","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Reinforcement Learning (RL)","Generative AI agents","RAG (Retrieval-Augmented Generation)","Python","PyTorch or TensorFlow for deep learning"],"x-skills-preferred":["game engines such as Unity and Unreal Engine","LLMs, transformers, diffusion models, and self-learning AI systems"],"datePosted":"2026-01-01T15:49:34.733Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Singapore"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Reinforcement Learning (RL), Generative AI agents, RAG (Retrieval-Augmented Generation), Python, PyTorch or TensorFlow for deep learning, game engines such as Unity and Unreal Engine, LLMs, transformers, diffusion models, and self-learning AI systems"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2cbb5108-1ad"},"title":"Senior Data Scientist","description":"<p>This Senior Data Scientist role will focus on designing and developing advanced AI-driven solutions for game developers and gamers. The ideal candidate will have strong expertise in Reinforcement Learning (RL), Generative AI agents, and Retrieval-Augmented Generation (RAG) to create intelligent gaming tools and experiences.</p>\n<p><strong>What you&#39;ll do</strong></p>\n<p>This role involves working closely with AI engineers, game developers, and software engineers to build cutting-edge AI capabilities that enhance game mechanics, player engagement, and content generation.</p>\n<ul>\n<li>Research, design, and implement rewards-based agents using Reinforcement Learning (RL) for testing gaming applications.</li>\n<li>Develop and optimize agents and advanced RAG-based solutions for dynamic game content creation, adaptive player interactions, and enhanced gaming experiences.</li>\n</ul>\n<p><strong>What you need</strong></p>\n<ul>\n<li>Strong background in Reinforcement Learning (RL), Generative AI agents, and RAG (Retrieval-Augmented Generation).</li>\n<li>Proficiency in Python and experience with PyTorch or TensorFlow for deep learning.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_2cbb5108-1ad","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Razer","sameAs":"https://razer.wd3.myworkdayjobs.com","logo":"https://logos.yubhub.co/razer.com.png"},"x-apply-url":"https://razer.wd3.myworkdayjobs.com/en-US/Careers/job/Singapore/AI-Data-Scientist_JR2025005484","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Reinforcement Learning","Generative AI agents","RAG","Python","PyTorch","TensorFlow"],"x-skills-preferred":["game engines","LLMs","transformers","diffusion models","self-learning AI systems"],"datePosted":"2025-12-26T10:52:23.649Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Singapore"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Reinforcement Learning, Generative AI agents, RAG, Python, PyTorch, TensorFlow, game engines, LLMs, transformers, diffusion models, self-learning AI systems"}]}