{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/multimodal"},"x-facet":{"type":"skill","slug":"multimodal","display":"Multimodal","count":54},"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_1ab22bcd-bdc"},"title":"Product Marketing Lead, GenAI","description":"<p>At Scale, we&#39;re looking for a Product Marketing Lead to join our team. As a Product Marketing Lead, you will own positioning and messaging for Scale&#39;s GenAI data products, articulating our differentiation on data quality, delivery speed, and multimodal breadth in a way that resonates with AI researchers and technical buyers.</p>\n<p>You will lead the content and social strategy for Scale Labs&#39; dedicated online presence, taking a research-native approach that earns attention and credibility from the AI community. You will build and maintain competitive intelligence and a sharp point of view on the data market, arming the team with differentiated positioning as the market evolves.</p>\n<p>You will partner with Scale Labs researchers to amplify published work - leaderboards, benchmarks, and research papers - and translate it into pipeline and demand generation for the GenAI business. You will develop go-to-market strategies for new data offerings and modalities, working closely with product and sales to drive awareness and build market momentum.</p>\n<p>You will collaborate cross-functionally with sales, engineering, and research to ensure consistent, compelling messaging across every customer touchpoint.</p>\n<p>Ideally, you&#39;d have 5+ years of experience in product marketing, with a track record of marketing technical products to developer or research audiences. You should have strong technical fluency and passion for AI, with the ability to hold a credible conversation about AI/ML fundamentals, training, and the role of data quality in model performance.</p>\n<p>You should also have experience building social-native content and community strategies on platforms like X, with an instinct for what resonates with technical practitioners. You should have excellent written communication and storytelling skills, with the ability to make complex technical concepts compelling without oversimplifying them.</p>\n<p>Nice to haves include familiarity with the AI training data market, or adjacent data and infrastructure spaces, as well as an existing network or relationships within the AI research 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_1ab22bcd-bdc","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/4675758005","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$155,200-$194,000 USD","x-skills-required":["product marketing","technical product marketing","AI/ML fundamentals","data quality","delivery speed","multimodal breadth","competitive intelligence","social media marketing","content strategy","community management"],"x-skills-preferred":["familiarity with AI training data market","adjacent data and infrastructure spaces","existing network or relationships within AI research community"],"datePosted":"2026-04-18T15:59:46.570Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; 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Vision</strong></p>\n<ul>\n<li>Set the Technical Roadmap: Define and own the technical strategy, architecture, and roadmap for Deep Research Agents for the Enterprise, ensuring alignment with Scale AI’s overall AI strategy and business goals.</li>\n</ul>\n<ul>\n<li>Drive Breakthrough Research to Production: Lead the end-to-end development, from initial research to production deployment, to landing on customer impact, with a focus on integrating diverse data modalities.</li>\n</ul>\n<ul>\n<li>Core Agent Capabilities Development:</li>\n</ul>\n<p><strong>Advanced Knowledge Retrieval</strong>: Architect and implement state-of-the-art retrieval systems to ensure the agents provide accurate and comprehensive answers from public and proprietary data sources from enterprises.</p>\n<p><strong>Data Analysis</strong>: Design and champion the development of data analysis agents that accurately translate complex natural language queries into executable SQL/code against diverse enterprise data schemas.</p>\n<p><strong>Multimodal Intelligence</strong>: Lead the integration of Multimodal AI capabilities to process and extract structured information from visual documents, tables, and forms, enriching the agent&#39;s knowledge base.</p>\n<p><strong>Architecture &amp; Design</strong>: Design and champion highly scalable, reliable, and low-latency infrastructure and frameworks for building, orchestrating, and evaluating multi-agent systems at enterprise scale.</p>\n<p><strong>Technical Excellence</strong>: Serve as the technical authority for the team, leading design reviews, defining ML engineering best practices, and ensuring code quality, security, and operational excellence for all agent systems.</p>\n<p><strong>Team Leadership &amp; Mentorship</strong></p>\n<ul>\n<li>Lead and Mentor: Technically lead and mentor a team of Machine Learning Engineers and Research Scientists, fostering a culture of innovation, rigorous engineering, rapid iteration, and technical depth.</li>\n</ul>\n<ul>\n<li>Recruiting &amp; Growth: Partner with management to hire, onboard, and grow top-tier talent, helping to shape the long-term structure and capabilities of the team.</li>\n</ul>\n<ul>\n<li>Cross-Functional Influence: Collaborate effectively with Product Managers, Data Scientists, and other engineering/science teams to translate ambiguous, high-level business problems into concrete, executable technical specifications and impactful agent solutions.</li>\n</ul>\n<p><strong>Basic Qualifications</strong></p>\n<ul>\n<li>Bachelor&#39;s degree in Computer Science, Electrical Engineering, a related field, or equivalent practical experience.</li>\n</ul>\n<ul>\n<li>8+ years of experience in software development, with at least 6 years focused on Machine Learning, Deep Learning, or Applied Research in a production environment.</li>\n</ul>\n<ul>\n<li>2+ years of experience in a formal or informal Technical Leadership role (Team Lead, Tech Lead) with a focus on setting technical direction for a domain.</li>\n</ul>\n<ul>\n<li>Deep expertise in Generative AI and Large Language Models (LLMs).</li>\n</ul>\n<ul>\n<li>Demonstrated experience designing, building, and deploying AI Agents or complex Agentic systems in production at scale.</li>\n</ul>\n<ul>\n<li>Experience with large-scale distributed systems and real-time data processing.</li>\n</ul>\n<p><strong>Preferred Qualifications</strong></p>\n<ul>\n<li>Advanced degree (Master&#39;s or Ph.D.) in Computer Science, Machine Learning, or a related quantitative field.</li>\n</ul>\n<ul>\n<li>Demonstrated experience designing and deploying production-grade Text-to-SQL systems, including handling complex schema linking and query optimization.</li>\n</ul>\n<ul>\n<li>Practical experience with Multimodal AI, specifically integrating OCR and vision-language models for document intelligence and structured data extraction from images/forms.</li>\n</ul>\n<ul>\n<li>Proven experience in one or more relevant deep research areas: Reinforcement Learning (RL), Reasoning and Planning, Agentic Systems.</li>\n</ul>\n<ul>\n<li>Experience with vector databases and advanced retrieval techniques.</li>\n</ul>\n<ul>\n<li>A track record of publishing research papers in top-tier ML/AI conferences (e.g., NeurIPS, ICML, ICLR, KDD).</li>\n</ul>\n<ul>\n<li>Excellent written and verbal communication skills, with the ability to articulate complex technical vision to executive stakeholders and technical peers.</li>\n</ul>\n<ul>\n<li>Experience driving cross-team technical initiatives that have delivered significant business impact.</li>\n</ul>\n<p><strong>Compensation</strong></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’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><strong>About Us</strong></p>\n<p>At Scale, our mission is to develop reliable AI systems for the world&#39;s most important decisions. Our products provide the high-quality data and full-stack technologies that power the world&#39;s leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. 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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_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_7e28478b-c37"},"title":"Research, Audio Expertise","description":"<p>We&#39;re seeking a researcher to advance the frontier of audio capabilities. You&#39;ll explore how audio models enable more natural and efficient communication/collaboration, preserving more information and capturing user intent.</p>\n<p>This is a highly collaborative role. You&#39;ll work closely across pre-training, post-training, and product with world-class researchers, infrastructure engineers, and designers.</p>\n<p>As a researcher in this role, you&#39;ll be expected to:</p>\n<ul>\n<li>Own research projects on audio training, low-latency inference, and conversational responsiveness.</li>\n<li>Design and train large-scale models that natively support audio input and output.</li>\n<li>Investigate scaling behaviour such as how data, model size, and compute affect capability and efficiency.</li>\n<li>Build and maintain audio data pipelines, including preprocessing, filtering, segmentation, and alignment for training and evaluation.</li>\n<li>Collaborate with data and infrastructure teams to scale audio training efficiently across distributed systems.</li>\n<li>Publish and present research that moves the entire community forward.</li>\n</ul>\n<p>Share code, datasets, and insights that accelerate progress across industry and academia.</p>\n<p>This role blends fundamental research and practical engineering, as we do not distinguish between the two roles internally. You will be expected to write high-performance code and read technical reports.</p>\n<p>It&#39;s an excellent fit for someone who enjoys both deep theoretical exploration and hands-on experimentation, and who wants to shape the foundations of how AI learns.</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_7e28478b-c37","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Thinking Machines Lab","sameAs":"https://thinkingmachines.ai/","logo":"https://logos.yubhub.co/thinkingmachines.ai.png"},"x-apply-url":"https://job-boards.greenhouse.io/thinkingmachines/jobs/5002212008","x-work-arrangement":"onsite","x-experience-level":"mid|senior","x-job-type":"full-time","x-salary-range":"$350,000 - $475,000 USD","x-skills-required":["Python","PyTorch","TensorFlow","JAX","Machine Learning","Deep Learning","Distributed Compute Environments"],"x-skills-preferred":["Probability","Statistics","Real-time Inference","Streaming Architectures","Optimization for Low Latency","Large-Scale Audio or Multimodal Models","Speech, Audio, Voice, or Similar Areas"],"datePosted":"2026-04-18T15:57:29.075Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, TensorFlow, JAX, Machine Learning, Deep Learning, Distributed Compute Environments, Probability, Statistics, Real-time Inference, Streaming Architectures, Optimization for Low Latency, Large-Scale Audio or Multimodal Models, Speech, Audio, Voice, or Similar Areas","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":350000,"maxValue":475000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_cd02d1a1-0e8"},"title":"Communications Lead, Claude Code","description":"<p>We&#39;re looking for a Communications Lead to own comms for Claude Code. You&#39;ll sit on the Product Communications team, working day-to-day with the Claude Code product team, developer relations, and marketing.</p>\n<p>The media landscape for developer tools doesn&#39;t look like it did five years ago. We need someone who understands both traditional press and the channels where developers form opinions. You might have come up through an in-house comms team, or you might have run launches inside product marketing, handled press from a DevRel role, or found your way to this work from somewhere adjacent.</p>\n<p>You should be a Claude Code user yourself and know the product well.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Own communications for Claude Code, from the big launches to the steady rhythm of updates, community moments, and everything in between</li>\n<li>Build and maintain strong relationships with journalists, newsletter writers, podcasters, and creators covering dev tools and the AI ecosystem</li>\n<li>Lead cross-functional product launch communications, coordinating messaging across comms, marketing, developer relations, and product</li>\n<li>Advise leadership and DevRel when things move fast or catch fire, whether it’s an incident or a community thread</li>\n<li>Translate complex technical work into stories that land with developers and still make sense to broader audiences</li>\n<li>Develop messaging frameworks and content strategies that work across technical and non-technical audiences</li>\n<li>Prepare Claude Code engineers and product leads for external moments: podcasts, talks, press, etc.</li>\n<li>Think across channels (press, social, community, owned) and know which lever to pull for each moment</li>\n<li>Pay attention to what&#39;s actually working and build the program from there</li>\n</ul>\n<p>You may be a good fit if you:</p>\n<ul>\n<li>Have 8–12 years of experience in communications, PR, or developer marketing, with meaningful time focused on technical products or developer audiences</li>\n<li>Use Claude Code heavily and can talk specifically about how you use it in your day-to-day</li>\n<li>Are high-agency and low-ego, with a bias to action</li>\n<li>Write clearly and concisely, whether it&#39;s a launch post or a cross-functional update, a lot of context moves through this role and people need to be able to follow it</li>\n<li>Have a deep understanding of both traditional media channels and the emerging platforms where technical communities engage</li>\n<li>Are very online, follow the right people, know what&#39;s moving through Hacker News and developer social chatter, and catch things early</li>\n<li>Have real fluency in developer culture and know how trust gets earned there</li>\n</ul>\n<p>Strong candidates may also</p>\n<ul>\n<li>Have experience at developer tools companies, infrastructure products, or open source projects</li>\n<li>Have an existing network in developer media, technical journalism, or the creator space</li>\n<li>Have experience managing communications for AI or ML products</li>\n</ul>\n<p>The annual compensation range for this role is $185,000-$255,000 USD.</p>\n<p>Logistics</p>\n<ul>\n<li>Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience</li>\n<li>Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience</li>\n<li>Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position</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>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.</p>\n<p>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.</p>\n<p>How we&#39;re different</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>Come work with us!</p>\n<p>Anthropic is a public benefit corporation headquartered in San Francisco. 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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_45cde3e1-29d"},"title":"Applied AI Engineer, Enterprise GenAI","description":"<p>We&#39;re looking for an Applied AI Engineer to join our Enterprise Engineering team. As an Applied AI Engineer, you&#39;ll work with clients to create ML solutions to satisfy their business needs. Your work will range from building next-generation AI cybersecurity firewalls to creating transformative AI experiences in journalism to applying foundation genomic models making predictions about life-saving drug proteins.</p>\n<p>Daily data-driven experiments will provide key insights around model strengths and inefficiencies which you&#39;ll use to improve your product&#39;s performance. You&#39;ll own, plan, and optimize the AI behind our Enterprise customer&#39;s deepest technical problems, leveraging our Scale Generative Platform (SGP) to build the most advanced AI agents across the industry.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Own, plan, and optimize the AI behind our Enterprise customer&#39;s deepest technical problems</li>\n<li>Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more</li>\n<li>Have experience gathering business requirements and translating them into technical solutions</li>\n<li>Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs</li>\n<li>Push production code in multiple development environments, writing and debugging code directly in both our customer&#39;s and Scale&#39;s codebases.</li>\n</ul>\n<p>Ideal candidate will have a love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client&#39;s business goals, a strong engineering background, deep familiarity with a data-driven approach when iterating on machine learning models, and experience working with cloud technology stack and developing machine learning models in a cloud environment.</p>\n<p>Nice to have: strong knowledge of software engineering best practices, experience building applications taking advantage of Generative AI in real, production use cases, and familiarity with state of the art LLMs and their strengths/weaknesses.</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_45cde3e1-29d","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/4514173005","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$216,000-$270,000 USD","x-skills-required":["Python","Machine Learning","Cloud Technology Stack","Data-Driven Approach","Software Engineering Best Practices"],"x-skills-preferred":["Generative AI","State of the Art LLMs","Multimodal Functionality","Tool-Calling"],"datePosted":"2026-04-18T15:56:38.201Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Machine Learning, Cloud Technology Stack, Data-Driven Approach, Software Engineering Best Practices, Generative AI, State of the Art LLMs, Multimodal Functionality, Tool-Calling","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":216000,"maxValue":270000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_0e93287d-e38"},"title":"Applied Research Engineer","description":"<p>Shape the Future of AI</p>\n<p>At Labelbox, we&#39;re building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we&#39;ve been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially.</p>\n<p>As an Applied Research Engineer at Labelbox, you will be at the forefront of developing cutting-edge systems and methods to create, analyze, and leverage high-quality human-in-the-loop data for frontier model developers. Your role will involve designing and implementing advanced systems that align human feedback into AI training processes, such as Reinforcement Learning from Human Feedback (RLHF), Direct Preference Optimization (DPO), etc. You will also work on innovative techniques to measure and improve human data quality, and develop AI-assisted tools to enhance the data labeling process.</p>\n<p>Your Impact</p>\n<ul>\n<li>Advance the field of AI alignment by developing cutting-edge methods, such as RLHF and novel approaches, that ensure AI systems reflect human preferences more accurately.</li>\n</ul>\n<ul>\n<li>Improve the quality of human-in-the-loop data by designing and deploying rigorous measurement and enhancement systems, leading to more reliable AI training.</li>\n</ul>\n<ul>\n<li>Increase efficiency and effectiveness in AI-assisted data labeling by creating tools that leverage active learning and adaptive sampling, reducing manual effort while improving accuracy.</li>\n</ul>\n<ul>\n<li>Shape the next generation of AI models by investigating how different types of human feedback (e.g., demonstrations, preferences, critiques) impact model performance and alignment.</li>\n</ul>\n<ul>\n<li>Optimize human feedback collection by developing novel algorithms that enhance how AI learns from human input, improving model adaptability and responsiveness.</li>\n</ul>\n<ul>\n<li>Bridge research and real-world application by integrating breakthroughs into Labelbox’s product suite, making human-AI alignment techniques scalable and impactful for users.</li>\n</ul>\n<ul>\n<li>Drive industry innovation by engaging with customers and the broader AI community to understand evolving data needs and share best practices for training frontier models.</li>\n</ul>\n<ul>\n<li>Contribute to the AI research ecosystem by publishing in top-tier journals, presenting at leading conferences, and influencing the future of human-centric AI.</li>\n</ul>\n<ul>\n<li>Stay ahead of AI advancements by continuously exploring new frontiers in human-AI collaboration, human data quality, and AI alignment, keeping Labelbox at the cutting edge.</li>\n</ul>\n<ul>\n<li>Establish Labelbox as a thought leader in AI by creating technical documentation, blog posts, and educational content that shape the industry&#39;s approach to human-centric AI development.</li>\n</ul>\n<p>What You Bring</p>\n<ul>\n<li>A strong foundation in AI and machine learning, backed by a Ph.D. or Master’s degree in Computer Science, Machine Learning, AI, or a related field.</li>\n</ul>\n<ul>\n<li>Proven experience (3+ years) in solving complex ML challenges and delivering impactful solutions that improve real-world AI applications.</li>\n</ul>\n<ul>\n<li>Expertise in designing and implementing data quality measurement and refinement systems that directly enhance model performance and reliability.</li>\n</ul>\n<ul>\n<li>A deep understanding of frontier AI models,such as large language models and multimodal models,and the human data strategies needed to optimize them.</li>\n</ul>\n<ul>\n<li>Proficiency in Python and experience with deep learning frameworks like PyTorch, JAX, or TensorFlow to prototype and develop cutting-edge solutions.</li>\n</ul>\n<ul>\n<li>A track record of publishing in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL) and contributing to the broader research community.</li>\n</ul>\n<ul>\n<li>The ability to bridge research and application by interpreting new findings and rapidly translating them into functional prototypes.</li>\n</ul>\n<ul>\n<li>Strong analytical and problem-solving skills that enable you to tackle ambiguous AI challenges with structured, data-driven approaches.</li>\n</ul>\n<ul>\n<li>Exceptional communication and collaboration skills, allowing you to work effectively across multidisciplinary teams and with external stakeholders.</li>\n</ul>\n<p>Labelbox Applied Research</p>\n<p>At Labelbox Applied Research, we&#39;re committed to pushing the boundaries of AI and data-centric machine learning, with a particular focus on advanced human-AI interaction techniques. We believe that high-quality human data and sophisticated human feedback integration methods are key to unlocking the next generation of AI capabilities. Our research team works at the intersection of machine learning, human-computer interaction, and AI ethics to develop innovative solutions that can be practically applied in real-world scenarios.</p>\n<p>We foster an environment of intellectual curiosity, collaboration, and innovation. We encourage our researchers to explore new ideas, engage in open discussions, and contribute to the wider AI community through publications and conference presentations. Our goal is to be at the forefront of human-centric AI development, setting new standards for how AI systems learn from and interact with humans.</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_0e93287d-e38","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Labelbox","sameAs":"https://www.labelbox.com/","logo":"https://logos.yubhub.co/labelbox.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/labelbox/jobs/4640965007","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$250,000-$300,000 USD","x-skills-required":["AI","Machine Learning","Deep Learning","Python","PyTorch","JAX","TensorFlow","Data Quality Measurement","Refinement Systems","Human-AI Interaction","Frontier AI Models","Large Language Models","Multimodal Models"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:55:40.503Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco Bay Area"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AI, Machine Learning, Deep Learning, Python, PyTorch, JAX, TensorFlow, Data Quality Measurement, Refinement Systems, Human-AI Interaction, Frontier AI Models, Large Language Models, Multimodal Models","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":250000,"maxValue":300000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_231ce599-c30"},"title":"Staff Machine Learning Engineer, Content Quality Signals","description":"<p>We&#39;re seeking a Staff Machine Learning Engineer to join our Content Understanding team. As a key member of this team, you will lead modeling strategy for content understanding, including architecture selection, training approach, and evaluation methodology. You will design and ship production models that generate content signals such as embeddings and classifications used across multiple product surfaces. The ideal candidate will have significant industry experience building software and ML pipelines/systems, including technical leadership. They will have strong proficiency in Python and at least one ML stack such as PyTorch / TensorFlow, plus solid software engineering fundamentals. The role requires proven experience training and deploying ML models to production, including model versioning, rollouts, monitoring, and retraining strategies. The successful candidate will have deep hands-on experience in content understanding domains, such as computer vision, NLP, and multimodal/embedding models. 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The successful candidate will be able to provide technical leadership through design reviews, mentoring, and raising the quality bar for modeling and ML engineering practices.</p>\n<p>In addition to the above responsibilities, the successful candidate will be expected to:</p>\n<ul>\n<li>Collaborate with infra/platform teams to ensure scalable, reliable training/serving (latency, cost, observability, rollout safety).</li>\n<li>Partner with signal-consuming teams (ranking, retrieval, integrity, ads) to define signal contracts, adoption patterns, and success metrics.</li>\n<li>Own the full ML lifecycle: data/labeling strategy (human labels + weak supervision), training pipelines, offline evaluation, online experimentation, deployment, and monitoring/retraining.</li>\n<li>Provide technical leadership through design reviews, mentoring, and raising the quality bar for modeling and ML engineering practices.</li>\n</ul>\n<p>Nice to have: experience with Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring; familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration.</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_231ce599-c30","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Pinterest","sameAs":"https://www.pinterest.com/","logo":"https://logos.yubhub.co/pinterest.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/pinterest/jobs/7531060","x-work-arrangement":"remote","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$189,308-$389,753 USD","x-skills-required":["Python","PyTorch","TensorFlow","Computer Vision","NLP","Multimodal Embedding Models","Large-Scale Datasets","Distributed Compute"],"x-skills-preferred":["Cursor","Copilot","Codex","LLM-Powered Productivity Tools"],"datePosted":"2026-04-18T15:54:53.925Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, US; Remote, US"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, TensorFlow, Computer Vision, NLP, Multimodal Embedding Models, Large-Scale Datasets, Distributed Compute, Cursor, Copilot, Codex, LLM-Powered Productivity Tools","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":189308,"maxValue":389753,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_4ced2159-802"},"title":"Research, Vision Expertise","description":"<p>Thinking Machines Lab is seeking a researcher to join their team in San Francisco. The successful candidate will work on advancing the science of visual perception and multimodal learning. They will design architectures that fuse pixels and text, build datasets and evaluation methods that test real-world comprehension, and develop representations that let models ground abstract concepts in the physical world.</p>\n<p>The ideal candidate will have expertise in multimodality and experience running large-scale experiments. They will be comfortable contributing to complex engineering systems and have a strong grasp of probability, statistics, and machine learning fundamentals.</p>\n<p>This is an evergreen role, meaning that the position is open on an ongoing basis. The company receives many applications, and there may not always be an immediate role that aligns perfectly with the candidate&#39;s experience and skills. However, they encourage candidates to apply and continuously review applications.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Own research projects on training and performance analysis of multimodal AI models.</li>\n<li>Curate and build large-scale datasets and evaluation benchmarks to advance vision capabilities.</li>\n<li>Work with data infrastructure engineers, pretraining researchers and engineers, and product teams to create frontier multimodal models and the products that leverage them.</li>\n<li>Publish and present research that moves the entire community forward.</li>\n</ul>\n<p>Skills and Qualifications:</p>\n<ul>\n<li>Ability to design, run, and analyze experiments thoughtfully, with demonstrated research judgment and empirical rigor.</li>\n<li>Understanding of machine learning fundamentals, large-scale training, and distributed compute environments.</li>\n<li>Proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow, or JAX).</li>\n<li>Comfortable with debugging distributed training and writing code that scales.</li>\n<li>Bachelor&#39;s degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding.</li>\n</ul>\n<p>Preferred qualifications include research or engineering contributions in visual reasoning, spatial understanding, or multimodal architecture design, experience developing evaluation frameworks for multimodal tasks, publications or open-source contributions in vision-language modeling, video understanding, or multimodal AI, and a strong grasp of probability, statistics, and ML fundamentals.</p>\n<p>Logistics:</p>\n<ul>\n<li>Location: San Francisco, California.</li>\n<li>Compensation: $350,000 - $475,000 USD per year, depending on background, skills, and experience.</li>\n<li>Visa sponsorship: Yes.</li>\n<li>Benefits: Generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.</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_4ced2159-802","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Thinking Machines Lab","sameAs":"https://thinkingmachines.ai/","logo":"https://logos.yubhub.co/thinkingmachines.ai.png"},"x-apply-url":"https://job-boards.greenhouse.io/thinkingmachines/jobs/5002288008","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$350,000 - $475,000 USD per year","x-skills-required":["Python","Deep learning framework (e.g., PyTorch, TensorFlow, or JAX)","Machine learning fundamentals","Large-scale training","Distributed compute environments"],"x-skills-preferred":["Visual reasoning","Spatial understanding","Multimodal architecture design","Evaluation frameworks for multimodal tasks","Vision-language 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home with us.</p>\n<p>This position reports to the Senior Manager of the NLP team and has the opportunity to be based in Vancouver, BC.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Research and develop state-of-the-art algorithms for autonomous voice agents, specifically focusing on real-time speech processing and reasoning loops.</li>\n</ul>\n<ul>\n<li>Advance DialpadGPT: Design and execute distributed training strategies to optimize our proprietary LLMs for agentic behaviors, including precise tool use, instruction following, and latency-constrained generation.</li>\n</ul>\n<ul>\n<li>Conduct rigorous evaluation and monitoring of model performances and troubleshoot issues with a keen understanding of resultant business impacts.</li>\n</ul>\n<ul>\n<li>Design and implement orchestration layers that effectively chain LLMs with external tools and APIs to solve complex customer problems autonomously.</li>\n</ul>\n<ul>\n<li>Work with large-scale multimodal datasets (text, audio) to improve model robustness and alignment.</li>\n</ul>\n<ul>\n<li>Collaborate with engineering, product, and design teams to deploy scalable, low-latency models and algorithms in production.</li>\n</ul>\n<ul>\n<li>Submit papers to top-tier academic conferences (ACL, EMNLP, NeurIPS) and contribute to the team’s research culture.</li>\n</ul>\n<p>To succeed in this role, you&#39;ll need:</p>\n<ul>\n<li>A Master’s or PhD degree in Computer Science, Machine Learning, Computational Linguistics, or a related quantitative field.</li>\n</ul>\n<ul>\n<li>2+ years of industry experience in Machine Learning/NLP for Master’s degree holders, or 1+ years for PhD holders.</li>\n</ul>\n<ul>\n<li>Deep understanding of LLMs: Demonstrated experience with training, fine-tuning (PEFT/LoRA), and alignment techniques (RLHF/DPO) for specific domains or tasks.</li>\n</ul>\n<ul>\n<li>Experience with Agentic Systems: Familiarity with building autonomous agents, including concepts like tool use, function calling, reasoning chains (CoT), and memory management.</li>\n</ul>\n<ul>\n<li>Strong proficiency in Python and PyTorch, with the ability to write clean, production-ready research code.</li>\n</ul>\n<ul>\n<li>Research Track Record: A history of publishing in top-tier conferences (ACL, EMNLP, NeurIPS, ICASSP) is highly valued.</li>\n</ul>\n<ul>\n<li>Multimodal Awareness: Familiarity with speech technologies (ASR, TTS) or processing real-time audio streams is a strong plus.</li>\n</ul>\n<ul>\n<li>Ability to bridge the gap between research and product, translating complex technical concepts into business value.</li>\n</ul>\n<ul>\n<li>Familiarity with version control tools like Git for collaborative projects.</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_d3b1dbb2-6ce","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Dialpad","sameAs":"https://dialpad.com","logo":"https://logos.yubhub.co/dialpad.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/dialpad/jobs/8508615002","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$161,500-$191,500 CAD","x-skills-required":["Machine Learning","Natural Language Processing","Python","PyTorch","LLMs","Agentic Systems","Speech Technologies","Version Control Tools"],"x-skills-preferred":["Research Track Record","Multimodal Awareness","Ability to Bridge Research and Product"],"datePosted":"2026-04-18T15:52:21.770Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Vancouver, Canada"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, Natural 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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_d94b43ab-0e0"},"title":"Research Scientist, Information Quality","description":"<p><strong>Job Title</strong></p>\n<p>Research Scientist, Information Quality</p>\n<p><strong>Job Description</strong></p>\n<p>This role requires a passion for advancing information literacy through AI &amp; machine learning, focusing on assessing media trustworthiness (images, audio, and video) and exploring concepts like authenticity, provenance, and context.</p>\n<p>Key responsibilities include formulating metrics, simulations, rapid prototyping of ML techniques, exploratory data analysis, collaborating with product teams to drive research, and developing tools and frameworks to accelerate research. A public example of research work is Backstory.</p>\n<p><strong>About Us</strong></p>\n<p>Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence.</p>\n<p><strong>The Role</strong></p>\n<p>To succeed in this role, you will need to be passionate about advancing information literacy using machine learning and other computational techniques. You&#39;ll join an interdisciplinary team of domain experts, ML researchers, and engineers to conduct cutting-edge research and advance the next generation of multimodal AI assistants that help co-investigation and deliberation.</p>\n<p>Relevant domains may include, but are not limited to, determining media authenticity, context discovery, and open source intelligence investigations. A public example of recent work is Backstory.</p>\n<p>Key responsibilities:</p>\n<ul>\n<li>Drive the projects by defining key research questions.</li>\n<li>Design, implement, and evaluate experiments to provide clear answers</li>\n<li>Contribute to real world impact, by landing your research in Google products and services.</li>\n<li>Publish research findings in top academic conferences and journals</li>\n<li>Stay up-to-date with the latest advancements in the field</li>\n<li>Collaborate with internal and external scientific domain experts.</li>\n</ul>\n<p><strong>About You</strong></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 in Computer Science, Statistics, or a related field.</li>\n<li>Strong publication record in top machine learning and/or computer vision conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV).</li>\n<li>Expertise in one or more of the following areas: social impact of AI, reinforcement learning, multimodal agents, computer vision, natural language understanding.</li>\n</ul>\n<p>In addition, the following would be an advantage:</p>\n<ul>\n<li>Passion for research on societal benefits and implications of the internet and AI with focus in information literacy.</li>\n<li>Experience with training, evaluating, and interpreting large language models.</li>\n<li>Experience working with large and noisy datasets.</li>\n<li>Experience collaborating across fields.</li>\n<li>Proven ability to design and execute independent research projects.</li>\n</ul>\n<p>When assessing technical background we will take a holistic view of the mix of scientific, ML and computational experience. We do not expect you to be an expert in all fields simultaneously. At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact.</p>\n<p>We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law.</p>\n<p>If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.</p>\n<p>The US base salary range for this full-time position is between $174,000 USD - $252,000 USD + bonus + equity + benefits.</p>\n<p>Your recruiter can share more about the specific salary range for your targeted location during the hiring process.</p>\n<p>Application deadline: April 28th, 2026</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_d94b43ab-0e0","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/7408812","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$174,000 USD - $252,000 USD + bonus + equity + benefits","x-skills-required":["PhD in Computer Science, Statistics, or a related field","Strong publication record in top machine learning and/or computer vision conferences or journals","Expertise in one or more of the following areas: social impact of AI, reinforcement learning, multimodal agents, computer vision, natural language understanding"],"x-skills-preferred":["Passion for research on societal benefits and implications of the internet and AI with focus in information literacy","Experience with training, evaluating, and interpreting large language models","Experience working with large and noisy datasets","Experience collaborating across fields","Proven ability to design and execute independent research projects"],"datePosted":"2026-04-18T15:39:36.602Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View, California, US; San Francisco, California, US"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"PhD in Computer Science, Statistics, or a related field, Strong publication record in top machine learning and/or computer vision conferences or journals, Expertise in one or more of the following areas: social impact of AI, reinforcement learning, multimodal agents, computer vision, natural language understanding, Passion for research on societal benefits and implications of the internet and AI with focus in information literacy, Experience with training, evaluating, and interpreting large language models, Experience working with large and noisy datasets, Experience collaborating across fields, Proven ability to design and execute independent research projects","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":174000,"maxValue":252000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_8a80575f-e9a"},"title":"Research Engineer, Information Quality","description":"<p><strong>Job Title</strong></p>\n<p>Research Engineer, Information Quality</p>\n<p><strong>Summary</strong></p>\n<p>At Google DeepMind, our research team is dedicated to tackling the most complex challenges in online information quality. We strive to advance the state of the art by developing innovative solutions to detect manipulated media and misleading narratives, ensuring the integrity of digital discourse.</p>\n<p><strong>Responsibilities</strong></p>\n<p>To succeed in this role, you will need to be passionate about advancing information literacy using machine learning and other computational techniques. You&#39;ll join an interdisciplinary team of domain experts, ML researchers, and engineers to research and build systems and tools to assess the trustworthiness of media (images, audio, and videos) on the internet.</p>\n<p>Key responsibilities:</p>\n<ul>\n<li>Plan and perform rapid prototyping of machine learning techniques applied to determining authenticity of media information.</li>\n<li>Undertake exploratory analysis to inform experimentation and research directions.</li>\n<li>Engage with product teams to drive the development of our research.</li>\n<li>Implement tools, libraries, and frameworks to speed up and enable new research.</li>\n<li>Report and present research findings, software developments, experimental results, and data analysis clearly and efficiently.</li>\n<li>Collaborate with internal and external scientific domain experts.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<p>In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:</p>\n<ul>\n<li>Master’s degree in Computer Science, Electrical Engineering, Science, or Mathematics, or equivalent experience.</li>\n<li>Applied experience with machine learning, preferably modern deep learning techniques (e.g., Transformers, Diffusion, LLMs).</li>\n<li>Programming experience.</li>\n<li>Quantitative skills in math and statistics.</li>\n<li>Experience exploring, analysing and visualising data.</li>\n</ul>\n<p><strong>Preferred Qualifications</strong></p>\n<p>In addition, the following would be an advantage:</p>\n<ul>\n<li>Experience in multimodal learning, including the training and deployment of large-scale models.</li>\n<li>Experience developing AI agents.</li>\n<li>Experience with Large Language Models, prompt engineering, few-shot learning, post-training techniques, and evaluations.</li>\n<li>A proven track record of research or engineering achievements, such as publications in peer-reviewed conferences or journals.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<p>The US base salary range for this full-time position is between $174,000 USD - $252,000 USD + bonus + equity + 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_8a80575f-e9a","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/7171371","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$174,000 USD - $252,000 USD + bonus + equity + benefits","x-skills-required":["Machine Learning","Deep Learning","Python","Quantitative Skills","Data Analysis"],"x-skills-preferred":["Multimodal Learning","AI Agents","Large Language Models","Prompt Engineering","Few-Shot Learning"],"datePosted":"2026-04-18T15:38:22.330Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View, California, US"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, Deep Learning, Python, Quantitative Skills, Data Analysis, Multimodal Learning, AI Agents, Large Language Models, Prompt Engineering, Few-Shot Learning","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":174000,"maxValue":252000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_e121da52-304"},"title":"Research Engineer, Human Understanding","description":"<p>We are seeking a highly motivated Research Engineer with a strong background in multi-modal modelling for humans and a focus on speech &amp; audio/visual to join the effort within Google DeepMind&#39;s Frontier AI unit.</p>\n<p>This role is pivotal in developing foundational multimodal AI capabilities to understand, generate, and protect human likeness. As a key contributor, you will design and implement cutting-edge models and frameworks, pushing the boundaries of AI to enable foundational capabilities for human-centric understanding and generation.</p>\n<p>This is a unique opportunity to contribute to impactful research and advance Google DeepMind&#39;s mission towards Artificial General Intelligence (AGI).</p>\n<p><strong>Key Responsibilities</strong></p>\n<ul>\n<li>Advance multimodal human representations &amp; understanding: Research and implement novel models and other multimodal techniques for a more holistic understanding of humans across visual, audio, and textual data.</li>\n<li>Conduct applied research: Conduct experimental research cycles from hypothesis to deployment.</li>\n<li>Drive technical projects: Take ownership of substantial technical projects within the effort, from ideation and design to implementation and evaluation, often involving cross-functional collaboration.</li>\n<li>Contribute to Infrastructure: Inform and contribute to the development of scalable and efficient research infrastructure for multimodal human understanding models and datasets.</li>\n<li>Design and execute strategies for tuning and adapting VLMs and other foundation models for specific tasks</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>PhD degree in Computer Science, Machine Learning, or a related technical field with 3+ years of relevant experience.</li>\n<li>Experience in developing machine learning models, such as audio &amp; speech-visual models.</li>\n<li>Experience in working with and tuning large-scale vision language models.</li>\n<li>Strong programming skills in Python and experience with at least one major deep learning framework (e.g., JAX)</li>\n<li>Experience conducting independent research and development, including experimental design, implementation, and analysis.</li>\n</ul>\n<p><strong>Salary</strong></p>\n<p>The US base salary range for this full-time position is between $174,000 USD - $252,000 USD + bonus + equity + 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_e121da52-304","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/7669433","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$174,000 USD - $252,000 USD","x-skills-required":["Python","JAX","Machine Learning","Deep Learning","Vision Language Models","Audio & Speech-Visual Models"],"x-skills-preferred":["Generative AI","Reinforcement Learning","Alignment Methods","Multimodal Learning","Privacy-Preserving Machine Learning"],"datePosted":"2026-04-18T15:38:13.994Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Los Angeles, California, US; Mountain View, California, US"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, JAX, Machine Learning, Deep Learning, Vision Language Models, Audio & Speech-Visual Models, Generative AI, Reinforcement Learning, Alignment Methods, Multimodal Learning, Privacy-Preserving Machine Learning","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":174000,"maxValue":252000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_28b01ce3-8a3"},"title":"Member of Technical Staff - Imagine Model","description":"<p>As a Member of Technical Staff on the Imagine Model Team, you will develop cutting-edge AI experiences beyond text, with a strong focus on enabling high-fidelity understanding and generation across image and video modalities, while also incorporating audio where it enhances visual content.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Create and drive engineering agendas to advance multimodal capabilities, with emphasis on image and video generation, editing, understanding, controllable/long-horizon synthesis, agentic planning, RL training, and world simulation (including audio integration for richer video experiences).</li>\n<li>Improve data quality through annotation, filtering, augmentation, synthetic generation, captioning, and in-depth data studies, particularly for visual and audio data.</li>\n<li>Design evaluation frameworks, metrics, benchmarks, evals, and reward models tailored to image/video/audio quality and coherence.</li>\n<li>Implement efficient algorithms for state-of-the-art model performance, including real-time inference, distillation, and scalable serving for visual content.</li>\n<li>Develop scalable data collection and processing pipelines for multimodal (primarily image/video-focused) datasets.</li>\n<li>Collaborate cross-functionally to integrate AI solutions into production and rapidly iterate based on user feedback.</li>\n</ul>\n<p>Basic Qualifications:</p>\n<ul>\n<li>Track record in leading studies that significantly improve neural network capabilities and performance through better data or modeling.</li>\n<li>Experience in data-driven experiment designs, systematic analysis, and iterative model debugging.</li>\n<li>Experience developing or working with large-scale distributed machine learning systems.</li>\n<li>Ability to deliver optimal end-to-end user experiences.</li>\n<li>Hands-on contributor with initiative, excellence, strong work ethic, prioritization skills, and excellent communication.</li>\n</ul>\n<p>Preferred Skills and Experience:</p>\n<ul>\n<li>Experience in SFT, RL, evals, human/synthetic data collection, or agentic systems.</li>\n<li>Proficiency in Python, JAX/XLA, PyTorch, Rust/C++, Spark, Ray, and related large-scale frameworks.</li>\n<li>Domain expertise in multimodal applications such as graphics engines, rendering techniques, image/video understanding and generation, world models, real-time simulation, or controllable/long-horizon visual content creation (audio/speech processing or music/audio generation experience is a plus where it supports video).</li>\n<li>Experience with agentic RL training, controllable/long-horizon generation, or multimodal agents that reason and act across modalities (especially in visual domains).</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_28b01ce3-8a3","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/5051985007","x-work-arrangement":"hybrid","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$180,000 - $440,000 USD","x-skills-required":["Python","JAX/XLA","PyTorch","Rust/C++","Spark","Ray","multimodal applications","agentic systems","RL training","controllable/long-horizon generation"],"x-skills-preferred":["SFT","evals","human/synthetic data collection","graphics engines","rendering techniques","image/video understanding and generation","world models","real-time simulation"],"datePosted":"2026-04-18T15:24:12.847Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Palo Alto, CA; Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, JAX/XLA, PyTorch, Rust/C++, Spark, Ray, multimodal applications, agentic systems, RL training, controllable/long-horizon generation, SFT, evals, human/synthetic data collection, graphics engines, rendering techniques, image/video understanding and generation, world models, real-time simulation","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":180000,"maxValue":440000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_540ce49c-271"},"title":"Member of Technical Staff - Multimodal Understanding","description":"<p><strong>About the Role</strong></p>\n<p>You will join the multimodal team to push toward superhuman multimodal intelligence. Advance understanding and generation across modalities,image, video, audio, and text,spanning the full stack: data curation/acquisition, tokenizer training, large-scale pre-training, post-training/alignment, infrastructure/scaling, evaluation, tooling/demos, and end-to-end product experiences.</p>\n<p>Collaborate cross-functionally with pre-training, post-training, reasoning, data, applied, and product teams to deliver frontier capabilities in multimodal reasoning, world modeling, tool use, agentic behaviors, and interactive human-AI collaboration. Contribute to building models that can see, hear, reason about, and interact with the world in real time at unprecedented levels.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Design, build, and optimize large-scale distributed systems for multimodal pre-training, post-training, inference, data processing, and tokenization at web/petabyte scale.</li>\n<li>Develop high-throughput pipelines for data acquisition, preprocessing, filtering, generation, decoding, loading, crawling, visualization, and management (images, videos, audio + text).</li>\n<li>Advance multimodal capabilities including spatial-temporal compression, cross-modal alignment, world modeling, reasoning, emergent abilities, audio/image/video understanding &amp; generation, real-time video processing, and noisy data handling.</li>\n<li>Drive data quality and studies: curation (human/synthetic), filtering techniques, analysis, and scalable pipelines to support trillion-parameter models.</li>\n<li>Create evaluation frameworks, internal benchmarks, reward models, and metrics that capture real-world usage, failure modes, interactive dynamics, and human-AI synergy.</li>\n<li>Innovate on algorithms, modeling approaches, hardware/software/algorithm co-design, and scaling paradigms for state-of-the-art performance.</li>\n<li>Build research tooling, user-friendly interfaces, prototypes/demos, full-stack applications, and enable rapid iteration based on feedback.</li>\n<li>Work across the stack (pre-training → SFT/RL/post-training) to enable reasoning, tool calling, agentic behaviors, orchestration, and seamless real-time interactions.</li>\n</ul>\n<p><strong>Basic Qualifications</strong></p>\n<ul>\n<li>Hands-on experience with multimodal pre-training, post-training, or fine-tuning (vision, audio, video, or cross-modal).</li>\n<li>Expert-level proficiency in Python (core language), with strong experience in at least one of: JAX / PyTorch / XLA.</li>\n<li>Proven track record building or optimizing large-scale distributed ML systems (training/inference optimization, GPU utilization, multi-GPU/TPU setups, hardware co-design).</li>\n<li>Deep experience designing and running data pipelines at scale: curation, filtering, generation, quality studies, especially for noisy/real-world multimodal data.</li>\n<li>Strong fundamentals in evaluation design, benchmarks, reward modeling, or RL techniques (particularly for interactive/agentic behaviors).</li>\n<li>Proactive self-starter who thrives in high-intensity environments and is passionate about pushing multimodal AI frontiers.</li>\n<li>Willingness to own end-to-end initiatives and do whatever it takes to deliver breakthrough user experiences.</li>\n</ul>\n<p><strong>Preferred Skills and Experience</strong></p>\n<ul>\n<li>Experience leading major improvements in model capabilities through better data, modeling, algorithms, or scaling.</li>\n<li>Familiarity with state-of-the-art in multimodal LLMs, scaling laws, tokenizers, compression techniques, reasoning, or agentic systems.</li>\n<li>Proficiency in Rust and/or C++ for performance-critical components.</li>\n<li>Hands-on work with large-scale orchestration tools such as Spark, Ray, or Kubernetes.</li>\n<li>Background building full-stack tooling: performant interfaces, real-time research demos/apps, or end-to-end product ownership.</li>\n<li>Passion for end-to-end user experience in interactive, real-time multimodal AI systems.</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_540ce49c-271","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/5111374007","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$180,000 - $440,000 USD","x-skills-required":["Multimodal pre-training","Post-training","Fine-tuning","Python","JAX","PyTorch","XLA","Large-scale distributed ML systems","Data pipelines","Evaluation design","Benchmarks","Reward modeling","RL techniques"],"x-skills-preferred":["State-of-the-art in multimodal LLMs","Scaling laws","Tokenizers","Compression techniques","Reasoning","Agentic systems","Rust","C++","Spark","Ray","Kubernetes","Full-stack tooling"],"datePosted":"2026-04-18T15:23:05.119Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Palo Alto, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Multimodal pre-training, Post-training, Fine-tuning, Python, JAX, PyTorch, XLA, Large-scale distributed ML systems, Data pipelines, Evaluation design, Benchmarks, Reward modeling, RL techniques, State-of-the-art in multimodal LLMs, Scaling laws, Tokenizers, Compression techniques, Reasoning, Agentic systems, Rust, C++, Spark, Ray, Kubernetes, Full-stack tooling","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":180000,"maxValue":440000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d5b743bb-d8f"},"title":"Product Manager, AI Platforms","description":"<p>The AI Platform Product Manager will drive the strategy and execution of Shield AI&#39;s next-generation autonomy intelligence stack. This PM owns the product vision and roadmap for the Hivemind AI Platform, ensuring we can manufacture, govern, and field advanced world models, robotics foundation models, and vision-language-action systems safely and at scale.</p>\n<p>This role sits at the intersection of AI/ML, autonomy, model lifecycle, infrastructure, and product strategy. The PM partners closely with engineering, AI research, Hivemind Solutions, and field teams to deliver the tooling that enables sovereign autonomy, AI Factories at the edge, and continuous learning,capabilities that are central to Shield AI&#39;s strategic direction.</p>\n<p>This is a high-impact role for an experienced product leader excited to define how foundation models are trained, validated, governed, and deployed across thousands of autonomous systems in highly contested environments.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>AI Model Development &amp; Training Platform</li>\n</ul>\n<p>Own the roadmap for foundation model training workflows, including dataset ingestion, curation, labeling, synthetic data generation, domain model training, and distillation pipelines. Define requirements for world models, robotics models, and VLA-based training, evaluation, and specialization. Lead the evolution of MLOps capabilities in Forge, including data lineage, experiment tracking, model versioning, and scalable evaluation suites.</p>\n<ul>\n<li>Data, Simulation &amp; Synthetic Data Factory</li>\n</ul>\n<p>Define product requirements for synthetic data generation, simulation-integrated data flywheels, and automated scenario generation. Partner with Digital Twin, Simulation, and autonomy teams to convert natural-language mission inputs into data needs, training procedures, and model variants.</p>\n<ul>\n<li>Safe Deployment &amp; Model Governance</li>\n</ul>\n<p>Lead the development of model governance and auditability tooling, including model cards, dataset rights, lineage tracking, safety gates, and compliance evidence. Build guardrails and workflows to safely deploy models onto edge hardware in disconnected, GPS- or comms-denied environments. Partner with Safety, Certification, Cyber, and Engineering teams to ensure traceability and evaluation pipelines meet operational and accreditation requirements.</p>\n<ul>\n<li>Edge Deployment &amp; AI Factory Integration</li>\n</ul>\n<p>Partner with Pilot, EdgeOS, and hardware teams to integrate foundation-model-based perception and reasoning into autonomy behaviors. Define requirements for distillation, quantization, and inference tooling as part of the “three-computer” development and deployment model. Ensure closed-loop workflows between cloud model training and edge-native execution.</p>\n<ul>\n<li>Cross-Functional Leadership</li>\n</ul>\n<p>Collaborate with Engineering, Research, Product, Customer Engagement, and Solutions teams to ensure model outputs meet mission and platform constraints. Translate advanced AI capabilities into intuitive workflows that platform OEMs and partner nations can use to build sovereign AI factories. Sequence foundational capabilities that unblock autonomy, simulation, and customer-facing product teams.</p>\n<ul>\n<li>User &amp; Customer Impact</li>\n</ul>\n<p>Develop deep empathy for ML engineers, autonomy developers, and Solutions engineers who rely on the platform. Capture operational data gaps, mission-driven model needs, and domain-specific specialization requirements. Lead demos and onboarding for model-development capabilities across internal and external teams.</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_d5b743bb-d8f","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Shield AI","sameAs":"https://www.shield.ai","logo":"https://logos.yubhub.co/shield.ai.png"},"x-apply-url":"https://jobs.lever.co/shieldai/7886f437-2d5e-4616-8dcb-3dc488f1f585","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$190,000 - $290,000 a year","x-skills-required":["AI Model Development & Training Platform","Data, Simulation & Synthetic Data Factory","Safe Deployment & Model Governance","Edge Deployment & AI Factory Integration","Cross-Functional Leadership","User & Customer Impact","Strong engineering background","Deep understanding of foundation models, robotics models, multimodal models, MLOps, and training infrastructure","Experience managing complex products spanning data pipelines, cloud training clusters, model governance, and edge deployments","Proven success partnering with research teams to transition ML innovations into stable, production-grade workflows"],"x-skills-preferred":["Experience working on autonomy, robotics, embedded AI, or mission-critical systems","Hands-on familiarity with GPU infrastructure, distributed training, or data lakehouse architectures","Experience supporting defense, dual-use, or safety-critical AI systems","Background designing or operating AI Factory–style pipelines (data → training → evaluation → distillation → edge deployment)","Advanced degree in engineering, ML/AI, robotics, or a related field"],"datePosted":"2026-04-17T13:02:54.419Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Diego"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AI Model Development & Training Platform, Data, Simulation & Synthetic Data Factory, Safe Deployment & Model Governance, Edge Deployment & AI Factory Integration, Cross-Functional Leadership, User & Customer Impact, Strong engineering background, Deep understanding of foundation models, robotics models, multimodal models, MLOps, and training infrastructure, Experience managing complex products spanning data pipelines, cloud training clusters, model governance, and edge deployments, Proven success partnering with research teams to transition ML innovations into stable, production-grade workflows, Experience working on autonomy, robotics, embedded AI, or mission-critical systems, Hands-on familiarity with GPU infrastructure, distributed training, or data lakehouse architectures, Experience supporting defense, dual-use, or safety-critical AI systems, Background designing or operating AI Factory–style pipelines (data → training → evaluation → distillation → edge deployment), Advanced degree in engineering, ML/AI, robotics, or a related field","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":190000,"maxValue":290000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2bc207d0-89b"},"title":"Senior Machine Learning Engineer","description":"<p>We are seeking a Senior Machine Learning Research Engineer to join the Machine Learning Science (MLS) team, within the Computational Science department. The ideal candidate has a strong knowledge in designing and building deep learning (DL) pipelines, and expertise in creating reliable, scalable artificial intelligence/machine learning (AI/ML) systems in a cloud environment.</p>\n<p>The MLS team at Freenome develops DL models using massive-scale genomic data that presents significant challenges for current training paradigms. The Senior Machine Learning Research Engineer will primarily be responsible for developing and deploying the infrastructure needed to support development of such DL models: enabling distributed DL pipelines, optimising hardware utilisation for efficient training, and performing model optimisations.</p>\n<p>As part of an interdisciplinary R&amp;D team, they will work in close collaboration with machine learning scientists, computational biologists and software engineers to accelerate the development of state-of-the-art ML/AI models and help Freenome achieve its mission.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Implementing and refining DL pipelines on distributed computing platforms to enhance the speed and efficiency of DL operations, including model training, data handling, model management, and inference.</li>\n<li>Collaborating closely with ML scientists and software engineers to understand current challenges and requirements and ensure that the DL model development pipelines created are perfectly aligned with scientific goals and operational needs.</li>\n<li>Continuously monitoring, evaluating, and optimising DL model training pipelines for performance and scalability.</li>\n<li>Staying up to date with the latest advancements in AI, ML, and related technologies, and quickly learning and adapting new tools and frameworks, if necessary.</li>\n<li>Developing and maintaining robust and reproducible DL pipelines that guarantee that DL pipelines can be reliably executed, maintaining consistency and accuracy of results.</li>\n<li>Driving performance improvements across our stack through profiling, optimisation, and benchmarking. Implementing efficient caching solutions and debugging distributed systems to accelerate both training and evaluation pipelines.</li>\n<li>Acting as a bridge facilitating communication between the engineering and scientific teams, documenting and sharing best practices to foster a culture of learning and continuous improvement.</li>\n</ul>\n<p>Must-haves include:</p>\n<ul>\n<li>MS or equivalent experience in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Software Engineering, with an emphasis on AI/ML theory and/or practical development.</li>\n<li>5+ years of post-MS industry experience working on developing AI/ML software engineering pipelines.</li>\n<li>Proficiency in a general-purpose programming language: Python (preferred), Java, Julia, C, C++, etc.</li>\n<li>Strong knowledge of ML and DL fundamentals and hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, Jax or Scikit-learn.</li>\n<li>In-depth knowledge of scalable and distributed computing platforms that support complex model training (such as Ray or DeepSpeed) and their integration with ML developer tools like TensorBoard, Wandb, or MLflow.</li>\n<li>Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and how to deploy and manage AI/ML models and pipelines in a cloud environment.</li>\n<li>Understanding of containerisation technologies (e.g., Docker) and computing resource orchestration tools (e.g., Kubernetes) for deploying scalable ML/AI solutions.</li>\n<li>Proven track record of developing and optimising workflows for training DL models, large language models (LLMs), or similar for problems with high data complexity and volume.</li>\n<li>Experience managing large datasets, including data storage (such as HDFS or Parquet on S3), retrieval, and efficient data processing techniques (via libraries and executors such as PyArrow and Spark).</li>\n<li>Proficiency in version control systems (e.g., Git) and continuous integration/continuous deployment (CI/CD) practices to maintain code quality and automate development workflows.</li>\n<li>Expertise in building and launching large-scale ML frameworks in a scientific environment that supports the needs of a research team.</li>\n<li>Excellent ability to work effectively with cross-functional teams and communicate across disciplines.</li>\n</ul>\n<p>Nice-to-haves include:</p>\n<ul>\n<li>Experience working with large-scale genomics or biological datasets.</li>\n<li>Experience managing multimodal datasets, such as combinations of sequence, text, image, and other data.</li>\n<li>Experience GPU/Accelerator programming and kernel development (such as CUDA, Triton or XLA).</li>\n<li>Experience with infrastructure-as-code and configuration management.</li>\n<li>Experience cultivating MLOps and ML infrastructure best practices, especially around reliability, provisioning and monitoring.</li>\n<li>Strong track record of contributions to relevant DL projects, e.g. on github.</li>\n</ul>\n<p>The US target range of our base salary for new hires is $161,925 - $227,325. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.</p>\n<p>Freenome is proud to be an equal-opportunity employer, and we value diversity. 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You will lead, encourage, and develop world-class engineering and data teams distributed across Europe, Asia and the United States.</p>\n<p><strong>Key Responsibilities:</strong></p>\n<ul>\n<li>Architect and operationalize NVIDIA’s end-to-end data Inference Acceleration strategy, powering Inferencing and continuous performance improvements.</li>\n<li>Drive Strategic Implementations of TensorRT, VLLM and other accelerated frameworks for inference solutions for Edge and Enterprise devices: Lead Accelerated Computing efforts and solutions for key Metropolis verticals. Set up Proofs of Readiness (PORs) and guide their implementations.</li>\n<li>Leading customer solutions: Collaborate with major Metropolis OEMs and Partners to architect highly accelerated and optimized custom deep learning models and inference pipelines for their specific requirements. Offer direct customer support, including debugging, technical education, and handling customer inquiries for our Metropolis partner and customers. Responsible for drafting and finalizing SOWs with internal customers and partners.</li>\n<li>Performance Benchmarking: Orchestrate efforts to achieve leading performance results on industry benchmarks like MLPerf on various edge and Enterprise devices.</li>\n<li>Technical Leadership &amp; Influence: Function as a technical leader for deep learning across multiple teams, giving oversight and build support. Apply customer insights to influence the composition and structure of upcoming SOC / GPU deep learning hardware.</li>\n<li>Scaling the team: Strategically hiring to meet new demands while also mentoring and adjusting existing teams to new deep learning challenges.</li>\n<li>Representing Nvidia Deep learning solutions in webinars, conferences and partner events</li>\n</ul>\n<p><strong>Requirements:</strong></p>\n<ul>\n<li>Masters in Computer Science/Electrical Engineering or equivalent experience.</li>\n<li>A minimum of 8 years of meaningful involvement in machine learning/deep learning research or practical experience, coupled with 7+ years of leadership background and overall 15+ years of industry experience.</li>\n<li>Over 10 years of validated expertise in the embedded software sector, holding technical leadership positions accountable for delivering outstanding production software within a multifaceted setting.</li>\n<li>Deep Knowledge of GPU, CPU and dedicated deep learning architecture fundamentals and low-level performance optimizations using heterogeneous computing.</li>\n<li>Hands-on experience with VLMs, LLMs, or multimodal AI systems applied to perception, data triage, or automated labeling.</li>\n<li>Strong expertise in large-scale data processing, systems build, or machine learning pipelines.</li>\n<li>Strong communication, careful planning, and technical leadership capabilities.</li>\n</ul>\n<p><strong>Benefits:</strong></p>\n<ul>\n<li>Competitive salary package and benefits</li>\n<li>Eligible for equity</li>\n</ul>\n<p><strong>How to Apply:</strong></p>\n<p>Applications for this job will be accepted at least until March 13, 2026.</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_db67438e-963","directApply":true,"hiringOrganization":{"@type":"Organization","name":"NVIDIA","sameAs":"https://nvidia.wd5.myworkdayjobs.com","logo":"https://logos.yubhub.co/nvidia.com.png"},"x-apply-url":"https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Director--Metropolis-Accelerated-and-Inferencing-Software_JR2011299","x-work-arrangement":"onsite","x-experience-level":"executive","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Machine Learning","Deep Learning","GPU","CPU","Heterogeneous Computing","TensorRT","VLLM","Proof of Readiness","Customer Support","Technical Education","Performance Benchmarking","Technical Leadership","Team Scaling","Webinars","Conferences","Partner Events"],"x-skills-preferred":["VLMs","LLMs","Multimodal AI Systems","Perception","Data Triage","Automated Labeling","Large-Scale Data Processing","Systems Build","Machine Learning Pipelines"],"datePosted":"2026-03-09T20:43:31.482Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Santa Clara"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, Deep Learning, GPU, CPU, Heterogeneous Computing, TensorRT, VLLM, Proof of Readiness, Customer Support, Technical Education, Performance Benchmarking, Technical Leadership, Team Scaling, Webinars, Conferences, Partner Events, VLMs, LLMs, Multimodal AI Systems, Perception, Data Triage, Automated Labeling, Large-Scale Data Processing, Systems Build, Machine Learning Pipelines"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_930f14dd-03d"},"title":"Member of Technical Staff - Multimodal Safety - MAI Super Intelligence Team","description":"<p>As a Member of Technical Staff, Multimodal Safety, you will work to develop and implement cutting-edge safety methodologies for post-training multimodal large language models to be served to millions of users through Copilot every day.</p>\n<p>We work on the bleeding edge and leverage the most powerful pretrained models and algorithms, making it critical that we ensure our AI systems behave safely and align with organisational values.</p>\n<p>You will be responsible for designing novel safety evaluation frameworks, curating high-quality data for robust evaluations and training, prototyping new safety capabilities, and developing safety-focused fine-tuning algorithms.</p>\n<p>We&#39;re looking for outstanding individuals with deep expertise in multimodal AI safety who can translate research insights into practical solutions while being a strong communicator and collaborative teammate.</p>\n<p>The ideal candidate takes the initiative in exploring new safety methodologies and enjoys building world-class, trustworthy AI experiences in a fast-paced applied research environment.</p>\n<p>Microsoft&#39;s mission is to empower every person and every organisation on the planet to achieve more.</p>\n<p>As employees we come together with a growth mindset, innovate to empower others, and collaborate to realise our shared goals.</p>\n<p>Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.</p>\n<p>Responsibilities:</p>\n<p>Leverage expertise in multimodal safety to uncover potential risks and develop novel mitigation strategies, including alignment techniques and robustness improvements for multimodal large language models.</p>\n<p>Create and implement comprehensive evaluation frameworks and red-teaming methodologies to assess model safety across diverse scenarios, edge cases, and potential failure modes.</p>\n<p>Build automated safety testing systems, generalise safety solutions into repeatable frameworks, and write efficient code for safety pipelines and intervention systems.</p>\n<p>Maintain a user-oriented perspective by understanding safety needs from user perspectives, validating safety approaches through user research, and serving as a trusted advisor on multimodal safety matters.</p>\n<p>Track advances in multimodal safety research, identify relevant state-of-the-art techniques, and adapt safety algorithms to drive innovation in production systems serving millions of users.</p>\n<p>Embody our culture and values.</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_930f14dd-03d","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/member-of-technical-staff-multimodal-safety-mai-super-intelligence-team-3/","x-work-arrangement":"hybrid","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$119,800 - $234,700 per year","x-skills-required":["multimodal safety","diffusion models","image generation","video generation","audio generation","safety evaluation frameworks","red-teaming methodologies","automated safety testing systems","safety pipelines","intervention systems"],"x-skills-preferred":["multimodal LLM safety","evaluation frameworks","automated red-teaming","guardrail systems","safety pipelines","user-validated safety decisions"],"datePosted":"2026-03-08T22:19:30.911Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"multimodal safety, diffusion models, image generation, video generation, audio generation, safety evaluation frameworks, red-teaming methodologies, automated safety testing systems, safety pipelines, intervention systems, multimodal LLM safety, evaluation frameworks, automated red-teaming, guardrail systems, safety pipelines, user-validated safety decisions","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_a51375e8-30e"},"title":"Member of Technical Staff, Software Co-Design AI HPC Systems","description":"<p>Our team&#39;s mission is to architect, co-design, and productionize next-generation AI systems at datacenter scale. We operate at the intersection of models, systems software, networking, storage, and AI hardware, optimizing end-to-end performance, efficiency, reliability, and cost. Our work spans today&#39;s frontier AI workloads and directly shapes the next generation of accelerators, system architectures, and large-scale AI platforms. We pursue this mission through deep hardware–software co-design, combining rigorous systems thinking with hands-on engineering. The team invests heavily in understanding real production workloads large-scale training, inference, and emerging multimodal models and translating those insights into concrete improvements across the stack: from kernels, runtimes, and distributed systems, all the way down to silicon-level trade-offs and datacenter-scale architectures. This role sits at the boundary between exploration and production. You will work closely with internal infrastructure, hardware, compiler, and product teams, as well as external partners across the hardware and systems ecosystem. Our operating model emphasizes rapid ideation and prototyping, followed by disciplined execution to drive high-leverage ideas into production systems that operate at massive scale. In addition to delivering real-world impact on large-scale AI platforms, the team actively contributes to the broader research and engineering community. Our work aligns closely with leading communities in ML systems, distributed systems, computer architecture, and high-performance computing, and we regularly publish, prototype, and open-source impactful technologies where appropriate.</p>\n<p>About the Team</p>\n<p>We build foundational AI infrastructure that enables large-scale training and inference across diverse workloads and rapidly evolving hardware generations. Our work directly shapes how AI systems are designed, deployed, and scaled today and into the future. Engineers on this team operate with end-to-end ownership, deep technical rigor, and a strong bias toward real-world impact.</p>\n<p>Microsoft Superintelligence Team</p>\n<p>Microsoft Superintelligence team’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.</p>\n<p>This role is part of Microsoft AI’s Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models!</p>\n<p>Responsibilities</p>\n<p>Lead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks. Drive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements. Co-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems. Develop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps. Partner with compiler, kernel, and runtime teams to unlock the full performance of current and next-generation accelerators, including custom kernels, scheduling strategies, and memory optimizations. Influence and guide AI hardware design at system and silicon levels, including accelerator microarchitecture, interconnect topology, memory hierarchy, and system integration trade-offs. Lead cross-functional efforts to prototype, validate, and productionize high-impact co-design ideas, working across infrastructure, hardware, and product teams. Mentor senior engineers and researchers, set technical direction, and raise the overall bar for systems rigor, performance engineering, and co-design thinking across the organization.</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_a51375e8-30e","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-software-co-design-ai-hpc-systems-mai-superintelligence-team-3/","x-work-arrangement":"hybrid","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["AI accelerator or GPU architectures","Distributed systems and large-scale AI training/inference","High-performance computing (HPC) and collective communications","ML systems, runtimes, or compilers","Performance modeling, benchmarking, and systems analysis","Hardware–software co-design for AI workloads","Proficiency in systems-level programming (e.g., C/C++, CUDA, Python) and performance-critical software development"],"x-skills-preferred":["Experience designing or operating large-scale AI clusters for training or inference","Deep familiarity with LLMs, multimodal models, or recommendation systems, and their systems-level implications","Experience with accelerator interconnects and communication stacks (e.g., NCCL, MPI, RDMA, high-speed Ethernet or InfiniBand)","Background in performance modeling and capacity planning for future hardware generations","Prior experience contributing to or leading hardware roadmaps, silicon bring-up, or platform architecture reviews","Publications, patents, or open-source contributions in systems, architecture, or ML systems"],"datePosted":"2026-03-08T22:18:41.443Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AI accelerator or GPU architectures, Distributed systems and large-scale AI training/inference, High-performance computing (HPC) and collective communications, ML systems, runtimes, or compilers, Performance modeling, benchmarking, and systems analysis, Hardware–software co-design for AI workloads, Proficiency in systems-level programming (e.g., C/C++, CUDA, Python) and performance-critical software development, Experience designing or operating large-scale AI clusters for training or inference, Deep familiarity with LLMs, multimodal models, or recommendation systems, and their systems-level implications, Experience with accelerator interconnects and communication stacks (e.g., NCCL, MPI, RDMA, high-speed Ethernet or InfiniBand), Background in performance modeling and capacity planning for future hardware generations, Prior experience contributing to or leading hardware roadmaps, silicon bring-up, or platform architecture reviews, Publications, patents, or open-source contributions in systems, architecture, or ML systems"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c9975749-904"},"title":"Senior Applied Scientist","description":"<p>As a Senior Applied Scientist in the Multimedia Team, you will redefine how millions of users discover, consume, and create visual content. You will be at the heart of Bing Visual Search, Bing Image Creator, and our vast video indexing engine. Your mission is to build intelligent systems that understand the deep semantics of pixels and frames, enabling world-class image and video experiences that are fast, relevant, and inspiring.</p>\n<p>Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.</p>\n<p>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. This expectation is subject to local law and may vary by jurisdiction.</p>\n<p>Responsibilities\nVisual Intelligence Development: Build and deploy SOTA machine learning models for image classification, object detection, and video action recognition to power Bing’s multimedia features.</p>\n<p>Multimodal &amp; Generative AI: Lead the development of multimodal embeddings that align text and visual data, and leverage Generative AI (e.g., DALL-E, MAI models) to enhance content creation tools.</p>\n<p>Scale &amp; Optimization: Design robust feature-engineering pipelines to process billions of images and videos, ensuring low-latency inference in production services.</p>\n<p>Strategic Leadership: Embody Microsoft’s values by Creating Clarity in complex AI problems and Generating Energy across cross-functional teams of engineers and PMs.</p>\n<p>Responsible AI: Ensure all visual models adhere to strict Security, Privacy, and GDPR standards, specifically focusing on content moderation and bias detection in multimedia.</p>\n<p>Qualifications\nRequired Qualifications: Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ 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 2+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</p>\n<p>Mastery of Python and deep learning frameworks such as PyTorch or TensorFlow. Proven track record in Computer Vision (CV) or Multimedia Understanding, including work with large-scale visual datasets. Experience building and deploying live production systems at scale.</p>\n<p>Preferred Qualifications: PhD focused on Computer Vision, Video Analytics, or Multimodal Learning. Experience with big data tools like Spark/PySpark and Azure Machine Learning. Publications in top-tier venues such as CVPR, ICCV, or ACM Multimedia.</p>\n<p>This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances.</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_c9975749-904","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-14/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","PyTorch","TensorFlow","Computer Vision","Multimedia Understanding","Large-scale visual datasets","Live production systems"],"x-skills-preferred":["PhD in Computer Vision","Video Analytics","Multimodal Learning","Spark/PySpark","Azure Machine Learning","CVPR","ICCV","ACM Multimedia"],"datePosted":"2026-03-08T22:14:34.671Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Noida"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, TensorFlow, Computer Vision, Multimedia Understanding, Large-scale visual datasets, Live production systems, PhD in Computer Vision, Video Analytics, Multimodal Learning, Spark/PySpark, Azure Machine Learning, CVPR, ICCV, ACM Multimedia"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_cd1a0d16-311"},"title":"Member of Technical Staff, Software Co-Design AI HPC Systems","description":"<p>Our team&#39;s mission is to architect, co-design, and productionize next-generation AI systems at datacenter scale. We operate at the intersection of models, systems software, networking, storage, and AI hardware, optimizing end-to-end performance, efficiency, reliability, and cost.</p>\n<p>We pursue this mission through deep hardware–software co-design, combining rigorous systems thinking with hands-on engineering. The team invests heavily in understanding real production workloads large-scale training, inference, and emerging multimodal models and translating those insights into concrete improvements across the stack: from kernels, runtimes, and distributed systems, all the way down to silicon-level trade-offs and datacenter-scale architectures.</p>\n<p>This role sits at the boundary between exploration and production. You will work closely with internal infrastructure, hardware, compiler, and product teams, as well as external partners across the hardware and systems ecosystem. Our operating model emphasizes rapid ideation and prototyping, followed by disciplined execution to drive high-leverage ideas into production systems that operate at massive scale.</p>\n<p>In addition to delivering real-world impact on large-scale AI platforms, the team actively contributes to the broader research and engineering community. Our work aligns closely with leading communities in ML systems, distributed systems, computer architecture, and high-performance computing, and we regularly publish, prototype, and open-source impactful technologies where appropriate.</p>\n<p>Microsoft Superintelligence Team\nMicrosoft Superintelligence team’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.</p>\n<p>This role is part of Microsoft AI’s Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact.</p>\n<p>Responsibilities\nLead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks.</p>\n<p>Drive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements.</p>\n<p>Co-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems.</p>\n<p>Develop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps.</p>\n<p>Partner with compiler, kernel, and runtime teams to unlock the full performance of current and next-generation accelerators, including custom kernels, scheduling strategies, and memory optimizations.</p>\n<p>Influence and guide AI hardware design at system and silicon levels, including accelerator microarchitecture, interconnect topology, memory hierarchy, and system integration trade-offs.</p>\n<p>Lead cross-functional efforts to prototype, validate, and productionize high-impact co-design ideas, working across infrastructure, hardware, and product teams.</p>\n<p>Mentor senior engineers and researchers, set technical direction, and raise the overall bar for systems rigor, performance engineering, and co-design thinking across the organization.</p>\n<p>Qualifications\nBachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.</p>\n<p>Additional or Preferred Qualifications\nMaster’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor’s Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.</p>\n<p>Strong background in one or more of the following areas: AI accelerator or GPU architectures Distributed systems and large-scale AI training/inference High-performance computing (HPC) and collective communications ML systems, runtimes, or compilers Performance modeling, benchmarking, and systems analysis Hardware–software co-design for AI workloads Proficiency in systems-level programming (e.g., C/C++, CUDA, Python) and performance-critical software development.</p>\n<p>Proven ability to work across organizational boundaries and influence technical decisions involving multiple stakeholders. Experience designing or operating large-scale AI clusters for training or inference. Deep familiarity with LLMs, multimodal models, or recommendation systems, and their systems-level implications. Experience with accelerator interconnects and communication stacks (e.g., NCCL, MPI, RDMA, high-speed Ethernet or InfiniBand). Background in performance modeling and capacity planning for future hardware generations. Prior experience contributing to or leading hardware roadmaps, silicon bring-up, or platform architecture reviews. 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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&#39;re looking for engineers to join a new effort building AI-powered products and capabilities for cybersecurity. You&#39;ll work across the stack to prototype new ideas and build from the ground up.</p>\n<p>This role sits at the intersection of research, product, and go-to-market. You&#39;ll work closely with research teams to develop new model capabilities for security applications, prototype and iterate quickly to validate ideas, and engage directly with customers and partners to inform what we build. The right candidate has the technical depth to engage with research, the product instincts to know what&#39;s worth building, and the drive to move fast.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Prototype and build new AI-powered products for cybersecurity</li>\n</ul>\n<ul>\n<li>Iterate quickly based on customer feedback and what you learn</li>\n</ul>\n<ul>\n<li>Collaborate with research teams to identify and develop new model capabilities for security applications</li>\n</ul>\n<ul>\n<li>Engage directly with customers and partners to understand workflows and inform product direction</li>\n</ul>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Have 7+ years of experience as a software engineer</li>\n</ul>\n<ul>\n<li>Experience developing cybersecurity products</li>\n</ul>\n<ul>\n<li>Enjoy fast iteration and are energized by prototyping new ideas</li>\n</ul>\n<ul>\n<li>Have strong product instincts and enjoy defining what to build, not just how to build it</li>\n</ul>\n<ul>\n<li>Are comfortable working closely with research and go-to-market teams</li>\n</ul>\n<ul>\n<li>Have strong communication skills and can work effectively across functions</li>\n</ul>\n<p><strong>Strong candidates may also have:</strong></p>\n<ul>\n<li>Experience in incident response, reverse engineering, network analysis, penetration testing, or similar fields</li>\n</ul>\n<ul>\n<li>Experience working with AI/ML models and building products on top of them</li>\n</ul>\n<ul>\n<li>Experience building agentic applications</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<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>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. <strong>Guidance on Candidates&#39; AI Usage:</strong> Learn about our policy for using AI in our application process</p>\n<p>Interested in building your career at Anthropic? Get future opportunities by following us on LinkedIn and Twitter.</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_6aa46bac-783","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/5063007008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$320,000 - $405,000 USD","x-skills-required":["software engineer","cybersecurity products","AI/ML models","incident response","reverse engineering","network analysis","penetration testing"],"x-skills-preferred":["agentic applications","circuit-based interpretability","multimodal neurons","scaling laws","AI & compute","concrete problems in AI safety","learning from human preferences"],"datePosted":"2026-03-08T13:52:59.143Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA; Washington, DC"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"software engineer, cybersecurity products, AI/ML models, incident response, reverse engineering, network analysis, penetration testing, agentic applications, circuit-based interpretability, multimodal neurons, scaling laws, AI & compute, concrete problems in AI safety, learning from human preferences","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_4f29adab-596"},"title":"Model Policy Manager, Youth Well-being","description":"<p><strong>Job Posting</strong></p>\n<p><strong>Model Policy Manager, Youth Well-being</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>Safety Systems</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>Estimated Base Salary $207K – $295K • 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 Safety Systems team is at the forefront of OpenAI&#39;s mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency.</p>\n<p>The Model Policy team aligns model behavior with desired human values and norms. We co-design policy _with_ models and _for_ models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. Key focus areas include: catastrophic risk, mental health, teen safety and multimodal safety.</p>\n<p><strong>About the Role</strong></p>\n<p>Providing access to powerful AI models introduces a host of challenging questions when it comes to model safety: How do we define safe behavior for how a model should behave? To what end? How do we do this in such a way that is actionable, objective and sustains replicability?</p>\n<p>This is a senior role in which you’ll help shape policy creation and development at OpenAI and make an impact by helping ensure that our groundbreaking technologies do not create harm. The ideal candidate can identify and develop cohesive and thoughtful taxonomies of harm on high risk topics with a sense of urgency. They can balance internal and external input in making complex decisions, carefully think through trade-offs, and write principled, enforceable policies based on our values. Importantly, this role is embedded in our research teams and directly informs model training.</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>In this role, you’ll:</strong></p>\n<ul>\n<li>Design model policies that govern safe model behavior in an objective and defensible way - e.g. how should the model respond in risky/unsafe scenarios? What does unsafe mean? How do we achieve safety while preserving beneficial model capabilities?</li>\n</ul>\n<ul>\n<li>You will develop taxonomies that inform data collection campaigns, model behaviour and monitoring strategies and also toe the line between maximizing utility and preventing catastrophic risk.</li>\n</ul>\n<ul>\n<li>Lead prioritization for safety efforts across the company for new model launches, understanding and addressing technical and business trade-offs.</li>\n</ul>\n<ul>\n<li>Develop a broad range of subject matter expertise while maintaining agility across topics.</li>\n</ul>\n<ul>\n<li>You will work across many internal teams which will require high organizational acumen and confident decision making.</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Have extensive experience researching LLMs, ML, AI, tech policy, moral reasoning, and/or enjoy classification problems.</li>\n</ul>\n<ul>\n<li>Have extensive experience defining, refining and enforcing policies for ML models across training, evaluation, and deployment.</li>\n</ul>\n<ul>\n<li>Understand the practical challenges of translating policy into model behavior across the full training stack, and can incorporate these constraints into policy design.</li>\n</ul>\n<ul>\n<li>Can reason about the benefits and risks of open-ended problem spaces, generate novel approaches under ambiguity, and take full ownership of end-to-end solutions from concept through execution.</li>\n</ul>\n<p><strong>Most relevant publications:</strong></p>\n<ul>\n<li>Introducing HealthBench</li>\n</ul>\n<ul>\n<li>Preparing for future AI capabilities in biology</li>\n</ul>\n<ul>\n<li>Safety evaluations hub</li>\n</ul>\n<ul>\n<li>OpenAI GPT5 System Card</li>\n</ul>\n<ul>\n<li>Evaluating Fairness in ChatGPT</li>\n</ul>\n<ul>\n<li>Improving Model Safety Behavior with Rule-Based Rewards</li>\n</ul>\n<ul>\n<li>OpenAI Model Spec</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 of individuals from all walks of life.</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_4f29adab-596","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/2f942546-be42-4cd1-aca8-334ec8c61031","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$207K – $295K","x-skills-required":["LLMs","ML","AI","tech policy","moral reasoning","classification problems","policy design","model behavior","training stack"],"x-skills-preferred":["data collection campaigns","model behavior and monitoring strategies","catastrophic risk","mental health","teen safety","multimodal safety"],"datePosted":"2026-03-06T18:42:28.724Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"LLMs, ML, AI, tech policy, moral reasoning, classification problems, policy design, model behavior, training stack, data collection campaigns, model behavior and monitoring strategies, catastrophic risk, mental health, teen safety, multimodal safety","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":207000,"maxValue":295000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_325c968b-d59"},"title":"Inference Technical Lead, Sora","description":"<p><strong>Inference Technical Lead, Sora</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>Research</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$380K • 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<p><strong>Benefits</strong></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 Sora team is pioneering multimodal capabilities for OpenAI’s foundation models. We’re a hybrid research and product team focused on integrating multimodal functionalities into our AI products, ensuring they are reliable, user-friendly, and aligned with our mission of broad societal benefit.</p>\n<p><strong>About the Role</strong></p>\n<p>We’re looking for a GPU Inference Engineer to contribute to improvements in model serving efficiency for Sora. This is a high-impact role where you’ll drive initiatives to optimize inference performance and scalability. You’ll also be engaged in model design, to help assist our researchers in developing inference-friendly models.</p>\n<p>_<strong>This role is critical to scaling the team’s broader goals - it will directly enable leadership to focus on higher-leverage initiatives by building a stronger technical foundation.</strong>_</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Perform engineering efforts focused on improving model serving, inference performance, and system efficiency</li>\n</ul>\n<ul>\n<li>Drive optimizations from a kernel and data movement perspective to improve system throughput and reliability</li>\n</ul>\n<ul>\n<li>Partner closely with research and product teams to ensure our models perform effectively at scale</li>\n</ul>\n<ul>\n<li>Design, build, and improve critical serving infrastructure to support Sora’s growth and reliability needs</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Have deep expertise in model performance optimization, particularly at the inference layer</li>\n</ul>\n<ul>\n<li>Have a strong background in kernel-level systems, data movement, and low-level performance tuning</li>\n</ul>\n<ul>\n<li>Are excited about scaling high-performing AI systems that serve real-world, multimodal workloads</li>\n</ul>\n<ul>\n<li>Can navigate ambiguity, set technical direction, and drive complex initiatives to completion</li>\n</ul>\n<p>_<strong>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.</strong>_</p>\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_325c968b-d59","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/3c2d1178-777f-4613-a084-75a3d37cd1af","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$380K • Offers Equity","x-skills-required":["GPU Inference Engineer","Model Performance Optimization","Kernel-Level Systems","Data Movement","Low-Level Performance Tuning"],"x-skills-preferred":["AI Systems","Multimodal Workloads","Complex Initiatives","Technical Direction"],"datePosted":"2026-03-06T18:42:26.117Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"GPU Inference Engineer, Model Performance Optimization, Kernel-Level Systems, Data Movement, Low-Level Performance Tuning, AI Systems, Multimodal Workloads, Complex Initiatives, Technical Direction","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":380000,"maxValue":380000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2bfc37e4-bc3"},"title":"Researcher, Pretraining Safety","description":"<p><strong>Job Posting</strong></p>\n<p><strong>Researcher, Pretraining Safety</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>Safety Systems</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><strong>About the Team</strong></strong></p>\n<p>The Safety Systems team is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and is at the forefront of OpenAI&#39;s mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency.</p>\n<p>The Pretraining Safety team’s goal is to build safer, more capable base models and enable earlier, more reliable safety evaluation during training. We aim to:</p>\n<ol>\n<li><strong>Develop upstream safety evaluations</strong> that to monitor how and when unsafe behaviors and goals emerge;</li>\n</ol>\n<ol>\n<li><strong>Create safer priors</strong> through targeted pretraining and mid-training interventions that make downstream alignment more effective and efficient</li>\n</ol>\n<ol>\n<li><strong>Design safe-by-design architectures</strong> that allow for more controllability of model capabilities</li>\n</ol>\n<p>In addition, we will conduct the foundational research necessary for understanding how behaviors emerge, generalize, and can be reliably measured throughout training.</p>\n<p><strong><strong>About the Role</strong></strong></p>\n<p>The Pretraining Safety team is pioneering how safety is built into models before they reach post-training and deployment. In this role, you will work throughout the full stack of model development with a focus on pre-training:</p>\n<ul>\n<li>Identify safety-relevant behaviors as they first emerge in base models</li>\n</ul>\n<ul>\n<li>Evaluate and reduce risk without waiting for full-scale training runs</li>\n</ul>\n<ul>\n<li>Design architectures and training setups that make safer behavior the default</li>\n</ul>\n<ul>\n<li>Strengthen models by incorporating richer, earlier safety signals</li>\n</ul>\n<p>We collaborate across OpenAI’s safety ecosystem—from Safety Systems to Training—to ensure that safety foundations are robust, scalable, and grounded in real-world risks.</p>\n<p><strong><strong>In this role, you will:</strong></strong></p>\n<ul>\n<li>Develop new techniques to predict, measure, and evaluate unsafe behavior in early-stage models</li>\n</ul>\n<ul>\n<li>Design data curation strategies that improve pretraining priors and reduce downstream risk</li>\n</ul>\n<ul>\n<li>Explore safe-by-design architectures and training configurations that improve controllability</li>\n</ul>\n<ul>\n<li>Introduce novel safety-oriented loss functions, metrics, and evals into the pretraining stack</li>\n</ul>\n<ul>\n<li>Work closely with cross-functional safety teams to unify pre- and post-training risk reduction</li>\n</ul>\n<p><strong><strong>You might thrive in this role if you:</strong></strong></p>\n<ul>\n<li>Have experience developing or scaling pretraining architectures (LLMs, diffusion models, multimodal models, etc.)</li>\n</ul>\n<ul>\n<li>Are comfortable working with training infrastructure, data pipelines, and evaluation frameworks (e.g., Python, PyTorch/JAX, Apache Beam)</li>\n</ul>\n<ul>\n<li>Enjoy hands-on research — designing, implementing, and iterating on experiments</li>\n</ul>\n<ul>\n<li>Enjoy collaborating with diverse technical and cross-functional partners (e.g., policy, legal, training)</li>\n</ul>\n<ul>\n<li>Are data-driven with strong statistical reasoning and rigor in experimental design</li>\n</ul>\n<ul>\n<li>Value building clean, scalable research workflows and streamlining processes for yourself and others</li>\n</ul>\n<p><strong><strong>About OpenAI</strong></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_2bfc37e4-bc3","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/d829b701-5ee2-414f-8596-ef94911a168a","x-work-arrangement":"onsite","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$295K – $445K • Offers Equity","x-skills-required":["pretraining architectures","training infrastructure","data pipelines","evaluation frameworks","Python","PyTorch/JAX","Apache Beam","hands-on research","collaboration","data-driven","statistical reasoning"],"x-skills-preferred":["LLMs","diffusion models","multimodal models","safe-by-design architectures","training configurations","loss functions","metrics","evals"],"datePosted":"2026-03-06T18:36:25.493Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"pretraining architectures, training infrastructure, data pipelines, evaluation frameworks, Python, PyTorch/JAX, Apache Beam, hands-on research, collaboration, data-driven, statistical reasoning, LLMs, diffusion models, multimodal models, safe-by-design architectures, training configurations, loss functions, metrics, evals","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_0c89d6df-95f"},"title":"Developer Experience Engineer","description":"<p><strong>Developer Experience Engineer</strong></p>\n<p><strong>About the Team</strong></p>\n<p>The Developer Experience team at OpenAI has a singular focus: empowering developers globally. Our mission is to provide every developer and startup on the planet with the most delightful and seamless experience to integrate AI into their applications and products. We ensure developers have the tools, resources, and support they need to unlock AI’s full potential.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Developer Experience Engineer, you will create compelling technical content, developer tools, and sample applications designed to inspire developers and enable them to succeed with OpenAI’s APIs, platform, and products for developers.</p>\n<p>We’re looking for people who combine strong technical skills, creativity, and a passion for engaging with and empowering developers.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Develop demos and sample applications demonstrating cutting-edge integrations and best practices using reasoning models, multimodal capabilities, and agent tools.</li>\n</ul>\n<ul>\n<li>Create high-quality technical content—including tutorials, blog posts, videos, and code samples—to educate and inspire the developer community about our models, APIs, and Codex.</li>\n</ul>\n<ul>\n<li>Actively engage with and foster a vibrant local and global developer ecosystem around OpenAI’s platform.</li>\n</ul>\n<ul>\n<li>Represent OpenAI at developer events and online platforms, serving as a knowledgeable, approachable advocate for developers.</li>\n</ul>\n<ul>\n<li>Gather and synthesize developer feedback to inform and enhance our product roadmap.</li>\n</ul>\n<ul>\n<li>Collaborate cross-functionally with product, engineering, and marketing teams to ensure adoption and success of OpenAI’s developer tools and APIs.</li>\n</ul>\n<ul>\n<li>Contribute directly to improving and refining OpenAI’s developer interfaces and surfaces.</li>\n</ul>\n<ul>\n<li>Own challenges end-to-end, proactively addressing gaps and acquiring new skills to resolve complex issues.</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Are passionate about crafting exceptional developer experiences and creating inspirational technical content and projects.</li>\n</ul>\n<ul>\n<li>Bring a robust full-stack engineering background with demonstrated experience building innovative applications using AI and large language models (LLMs).</li>\n</ul>\n<ul>\n<li>Have strong user empathy and care deeply about delivering experiences developers truly appreciate.</li>\n</ul>\n<ul>\n<li>Have a proven track record of successfully creating engaging technical content, compelling demos, or innovative developer tooling that accelerates technology adoption.</li>\n</ul>\n<ul>\n<li>Find joy in coding, continuously shipping high-quality, impactful software.</li>\n</ul>\n<ul>\n<li>Excel in dynamic environments characterized by rapidly evolving priorities, ambiguity, and competing deadlines.</li>\n</ul>\n<ul>\n<li>Are an exceptional collaborator who thrives working cross-functionally and enjoys partnering with diverse teams.</li>\n</ul>\n<ul>\n<li>Maintain a genuine commitment to AI ethics and safety, strongly aligning with OpenAI&#39;s responsible AI development principles.</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_0c89d6df-95f","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/bc40de6b-6dbc-49ce-9fc4-d9728baa1ec6","x-work-arrangement":"remote","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$198K – $335K","x-skills-required":["full-stack engineering","AI","large language models (LLMs)","developer tools","sample applications","technical content","developer community","product roadmap","cross-functional collaboration","AI ethics and safety"],"x-skills-preferred":["innovative applications","cutting-edge integrations","best practices","multimodal capabilities","agent tools","developer events","online platforms","developer feedback","product development","software development"],"datePosted":"2026-03-06T18:33:59.222Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"full-stack engineering, AI, large language models (LLMs), developer tools, sample applications, technical content, developer community, product roadmap, cross-functional collaboration, AI ethics and safety, innovative applications, cutting-edge integrations, best practices, multimodal capabilities, agent tools, developer events, online platforms, developer feedback, product development, software development","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":198000,"maxValue":335000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_440a65d7-eed"},"title":"Software Engineer - Sensing, Consumer Products","description":"<p><strong>Software Engineer - Sensing, Consumer Products</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>Consumer Products</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$325K • 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<p><strong>Benefits</strong></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>Consumer Products Research prototypes the future of computing: we explore new modalities, interaction patterns, and system behaviors, then do the engineering required to make those ideas real in rigorous prototypes. The Neosensing team sits at the intersection of sensing, edge algorithms, and systems engineering. We build the end-to-end software that turns new signals into dependable capabilities—collection tooling and protocols, algorithm integration and evaluation hooks, and on-device loops that stay stable under real-world variability. We care deeply about software quality and iteration speed: clean interfaces, debuggability, observability, and performance under tight device constraints.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Software Engineer on Consumer Products Research, you’ll sit at the boundary between algorithm development and shippable systems. You’ll work closely with algorithm engineers to translate prototypes into clean interfaces, reliable pipelines, and efficient on-device implementations—with strong attention to performance, observability, and real-world failure modes.</p>\n<p>This is a software role first: we’re looking for someone who loves writing great code every day, takes pride in engineering craft, and is comfortable going deep enough into the algorithmic details to make the system work end-to-end.</p>\n<p><strong>This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees.</strong></p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Build and ship production software for sensing algorithms, translating algorithm prototypes into reliable end-to-end systems.</li>\n</ul>\n<ul>\n<li>Implement and own key parts of the Python shipping pipeline (integration surfaces, evaluation hooks, and quality/performance guardrails).</li>\n</ul>\n<ul>\n<li>Develop embedded/on-device software in an RTOS environment (e.g., Zephyr) and deploy models to device runtimes and hardware accelerators.</li>\n</ul>\n<ul>\n<li>Optimize real-time on-device perception loops (e.g., detection/tracking-style pipelines) for stability, latency, power, and memory constraints.</li>\n</ul>\n<ul>\n<li>Create data collection + instrumentation tooling to bring up new sensing modalities and accelerate iteration from prototype → dataset → model → device.</li>\n</ul>\n<ul>\n<li>Partner cross-functionally (algorithms, human data, firmware/hardware) to debug, profile, and harden systems against real-world variability.</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Love writing great software and want your work to sit close to novel sensing and edge algorithms.</li>\n</ul>\n<ul>\n<li>Understand algorithm behavior well enough to integrate, debug, and evaluate it—even if you’re not the primary model inventor.</li>\n</ul>\n<ul>\n<li>Have shipped production Python systems and care about clean interfaces, tests, and long-term maintainability.</li>\n</ul>\n<ul>\n<li>Enjoy embedded/on-device work and can debug across hardware, firmware, and higher-level application layers.</li>\n</ul>\n<ul>\n<li>Care about performance engineering and know how to profile and optimize under tight device constraints.</li>\n</ul>\n<ul>\n<li>Take ownership end-to-end and thrive in ambiguous, fast-moving, zero-to-one environments.</li>\n</ul>\n<p><strong>Bonus:</strong></p>\n<ul>\n<li>Zephyr (or similar RTOS) experience.</li>\n</ul>\n<ul>\n<li>On-device ML deployment (NPU/GPU/DSP) and accelerator-aware profiling/optimization.</li>\n</ul>\n<ul>\n<li>Background in multimodal sensing, sensor fusion, or on-device perception.</li>\n</ul>\n<ul>\n<li>Experience building data collection systems and human-in-the-loop workflows (protocols, QA, metadata)</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. 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If the role is non-exempt, overtime pay will be provided consistent with applicable laws. 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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. 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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>At Roblox, computer vision and graphics power the way our global community discovers, creates, and interacts on our virtual platform. This role involves building cutting-edge models to interpret and analyze every form of content—experiences, text, images, videos, and 3D avatars. Your work will directly influence core systems that drive the next generation of creation, search, recommendations, and trust &amp; safety initiatives across our massive ecosystem.</p>\n<p>We’re looking for PhD candidates passionate about the intersection of computer vision, graphics, and generative modeling. You’ll work on applied research and engineering projects with direct production impact — enabling new ways for creators and players to bring ideas to life.</p>\n<p><strong>Teams Hiring for This Role</strong></p>\n<ul>\n<li><strong>Content Understanding:</strong> Develop large-scale computer vision and multimodal models that classify, organize, and recommend 3D and visual content to improve user discovery, personalization, and safety.</li>\n</ul>\n<ul>\n<li><strong>Account Identity</strong> : focuses on various aspects of user Identity from bot detection, alternate account detection graph, to age estimation based on behavioral and facial features.</li>\n</ul>\n<p><strong>You Will:</strong></p>\n<ul>\n<li>Lead the research and development of deep learning models for visual content understanding and 3D content generation (image/video/3D scenes, avatars, and assets).</li>\n</ul>\n<ul>\n<li>Design and implement foundation models for visual and 3D-based creation, search, and recommendations, ensuring a high level of fidelity, relevance, and ranking.</li>\n</ul>\n<ul>\n<li>Break down complex product requirements into iterative deliverable stages, moving applied research into high-scale production systems.</li>\n</ul>\n<ul>\n<li>Implement innovative visual and multi-modal models that power core Roblox functions (e.g., world creation, avatar systems, search, and recommendations).</li>\n</ul>\n<ul>\n<li>Build high precision facial age estimation across demographics from ground up including various fraud detection techniques for a robust and safe user identity system.</li>\n</ul>\n<p><strong>You Have:</strong></p>\n<ul>\n<li>Possessing or pursuing a PhD in computer science, engineering, or a related field, with a thesis aligned to Roblox’s research areas.</li>\n</ul>\n<ul>\n<li>Expertise in one or more areas: computer vision, multimodal learning, 3D Graphics, or large-scale representation learning.</li>\n</ul>\n<ul>\n<li>Experience developing and training deep learning models using modern frameworks (PyTorch, TensorFlow, JAX).</li>\n</ul>\n<ul>\n<li>A strong research track record, evidenced by multiple publications and presentations in top-tier, peer-reviewed venues.</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 this page.</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_e13425ae-b83","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/7323437","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$195,780—$242,100 USD","x-skills-required":["computer vision","multimodal learning","3D Graphics","large-scale representation learning","PyTorch","TensorFlow","JAX","Python","C++","Go","Java"],"x-skills-preferred":[],"datePosted":"2026-03-06T14:19:13.911Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Mateo, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"computer vision, multimodal learning, 3D Graphics, large-scale representation learning, PyTorch, TensorFlow, JAX, Python, C++, Go, Java","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_5276e91e-221"},"title":"Senior Machine Learning Engineer, Recommendation Systems - PhD Early Career","description":"<p><strong>[2026] Senior Machine Learning Engineer, Recommendation Systems - PhD Early Career</strong></p>\n<p>San Mateo, CA, United States</p>\n<p>Early Career</p>\n<p>ID: 5471</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>We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.</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>Recommendation Systems are a key growth lever at Roblox, driving retention, engagement, and monetization for hundreds of millions of users. This role offers the unique opportunity to redefine how users search and discover everything from the most interesting immersive experiences and digital avatars in our Marketplace to personalized advertising. You will solve a diverse range of high-scale ranking, retrieval, and personalization problems across our platform.</p>\n<p>We combine cutting-edge research —including deep learning, generative AI, and reinforcement learning techniques— with large-scale engineering to bridge experimentation and production; you&#39;ll design algorithms that operate at massive scale and shape the next generation of recommender systems for user-generated content.</p>\n<p><strong>Teams Hiring for This Role</strong></p>\n<ul>\n<li><strong>Search:</strong> powers major recommendation surfaces—drives user engagement by redesigning core surfaces and search/homepage ranking</li>\n</ul>\n<ul>\n<li><strong>Notifications:</strong> owns the distributed systems and ML platform that transform billions of Roblox signals into high‑value notifications for hundreds of millions of players.</li>\n</ul>\n<ul>\n<li><strong>Economy:</strong> builds the ML backbone for marketplace, monetization, and commerce (including fraud, pricing, and bundling)</li>\n</ul>\n<ul>\n<li><strong>Ads &amp; Brands:</strong> focuses on ranking, retrieval, and marketplace/auction theory to optimize sponsored content delivery.</li>\n</ul>\n<ul>\n<li><strong>Safety, Alt Defense:</strong> architects a massive-scale detection engine that identifies recidivist bad actors across billions of accounts to ensure the long-term integrity of the Roblox community.</li>\n</ul>\n<p><strong>You Will</strong></p>\n<ul>\n<li>Design and implement large-scale recommendation systems that power discovery across Roblox’s surfaces — experiences, avatars, and creator content.</li>\n</ul>\n<ul>\n<li>Develop deep learning models for ranking, retrieval, and personalization using approaches in multimodal models, LLMs, and generative AI.</li>\n</ul>\n<ul>\n<li>Collaborate with applied researchers, engineers, and product teams to advance experimentation and accelerate innovation.</li>\n</ul>\n<ul>\n<li>Translate research into production systems that impact hundreds of millions of daily active users.</li>\n</ul>\n<ul>\n<li>Work backward from user and product needs to deliver ML solutions that drive engagement, retention, and ecosystem growth.</li>\n</ul>\n<p><strong>You Have</strong></p>\n<ul>\n<li>Possessing or pursuing a PhD in computer science, engineering, or a related field, with a thesis aligned to Roblox’s research areas.</li>\n</ul>\n<ul>\n<li>Expertise in one or more areas: recommender systems, search systems, information retrieval, or generative models (e.g., LLMs, VLMs, VLAs)</li>\n</ul>\n<ul>\n<li>Ability to design and architect systems for efficient personalization and user interest modeling using advanced attention mechanisms (e.g., sparse/linear attention).</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., SIGIR, KDD, RecSys, ICLR, 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\\_. 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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_5276e91e-221","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/7350081","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$195,780—$242,100 USD","x-skills-required":["recommender systems","search systems","information retrieval","generative models","deep learning","generative AI","reinforcement learning","multimodal models","LLMs","VLMs","VLAs","Python","C++","Go","Java"],"x-skills-preferred":["sparse/linear attention","top-tier, peer-reviewed venues","SIGIR","KDD","RecSys","ICLR","ICML","NeurIPS"],"datePosted":"2026-03-06T14:17:16.772Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Mateo, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"recommender systems, search systems, information retrieval, generative models, deep learning, generative AI, reinforcement learning, multimodal models, LLMs, VLMs, VLAs, Python, C++, Go, Java, sparse/linear attention, top-tier, peer-reviewed venues, SIGIR, KDD, RecSys, ICLR, ICML, NeurIPS","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_c29150ad-04e"},"title":"Member of Technical Staff, AI Multimodal","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Member of Technical Staff, AI Multimodal at their Zürich 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 a Member of Technical Staff, AI Multimodal, you will be responsible for developing algorithms, designing model architectures, conducting experiments, championing measurement and evaluation, innovating datasets and data pipelines. You will improve training and deployment efficiency, paying careful attention to detail, persevering, and learning from everyone’s attempts whether successful or not. You will follow a rigorous data-driven approach grounded in meticulous ablation studies and scientific analysis. You will innovate and iterate over ideas, prototypes, and product. You will collaborate closely with teams on infrastructure, data engineering, pre-training, post-training, and product feedback. You will advance the AI frontier responsibly. 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This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising AI-powered quality understanding and recommendation systems.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Principal Applied Scientist, you&#39;ll lead the science behind Discover&#39;s ranking and content-quality stack, combining LLMs, multimodal models, and large-scale recommender systems to drive measurable gains in engagement, satisfaction, and trust. You will set technical direction, mentor a high-caliber science cohort, and partner closely with engineering, PM, UXR, and policy to ship end-to-end outcomes.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Lead content-quality understanding at scale.</li>\n<li>Advance the recommendation &amp; ranking stack.</li>\n<li>Own evaluation and experimentation.</li>\n<li>Champion safety &amp; trust.</li>\n<li>Scale E2E ML systems.</li>\n<li>Mentor &amp; influence.</li>\n<li>Stay close to users.</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>6+ years related experience (e.g., statistics, predictive analytics, research).</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Expertise with LLMs (prompting, finetuning, RAG), multimodal modeling, and retrieval-augmented recommendation; familiarity with counterfactual learning and multi-objective optimization.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Demonstrated ability to lead cross-disciplinary efforts (PM, ENG, UXR, editorial/policy) from idea to shipped impact; mentoring scientists and setting technical vision.</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_3fe213ad-1b0","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-14/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"Competitive salary","x-skills-required":["LLMs","multimodal modeling","retrieval-augmented recommendation","counterfactual learning","multi-objective optimization"],"x-skills-preferred":["PyTorch","Azure ML","Kusto","Synapse","Azure AI Foundry"],"datePosted":"2026-03-06T07:31:53.651Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"LLMs, multimodal modeling, retrieval-augmented recommendation, counterfactual learning, multi-objective optimization, PyTorch, Azure ML, Kusto, Synapse, Azure AI Foundry"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_ef8ecae1-e0a"},"title":"Member of Technical Staff, AI Multimodal","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Member of Technical Staff, AI Multimodal at their Zürich 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 a Member of Technical Staff, AI Multimodal, you will be responsible for developing algorithms, designing model architectures, conducting experiments, championing measurement and evaluation, innovating datasets and data pipelines. You will improve training and deployment efficiency, paying careful attention to detail, persevering, and learning from everyone’s attempts whether successful or not. You will follow a rigorous data-driven approach grounded in meticulous ablation studies and scientific analysis. You will innovate and iterate over ideas, prototypes, and product. 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This role requires someone who can provide direct technical and strategic support to the CEO of Microsoft AI, identifying opportunities and risks across our research portfolio.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Technical Advisor, you will engage deeply with research teams on pre-training, post-training, multimodal systems, infrastructure, and safety/alignment work. You will prototype and evaluate models, techniques, and infrastructure to develop insights and inform strategic decisions. 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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>We seek exceptional individuals who bring proven expertise, demonstrated through impactful publications or technical leadership on high-scale projects. The role involves developing algorithms, designing model architectures, conducting experiments, championing measurement and evaluation, innovating datasets and data pipelines. You will improve training and deployment efficiency, paying careful attention to detail, persevering, and learning from everyone’s attempts whether successful or not. Follow a rigorous data-driven approach grounded in meticulous ablation studies and scientific analysis. Innovate and iterate over ideas, prototypes, and product. 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This role sits at the heart of crafting user experiences that highlight new applications of state-of-the-art AI models shaping the future. You&#39;ll work directly with AI researchers, product managers, and engineers to define requirements, scope projects, and deliver high-impact solutions.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Senior Software Engineer, you will play a key role in crafting user experiences that highlight new applications of state-of-the-art AI models shaping the future. Your primary responsibilities will include designing and delivering end-to-end consumer AI experiences and internal tools while building secure, scalable platform services that power multiple AI-driven products. You will work closely with AI researchers, product managers, and engineers to define requirements, scope projects, and deliver high-impact solutions. You will also build and optimize data pipelines for collecting, processing, and analyzing large volumes of data used for training and evaluating AI models.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Design and deliver end-to-end consumer AI experiences and internal tools while building secure, scalable platform services that power multiple AI-driven products.</li>\n<li>Work closely with AI researchers, product managers, and engineers to define requirements, scope projects, and deliver high-impact solutions.</li>\n<li>Build and optimize data pipelines for collecting, processing, and analyzing large volumes of data used for training and evaluating AI models.</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>5+ years of experience in software development, with a focus on building end-to-end AI consumer products.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Experience using Machine Learning frameworks, including experience using, deploying, and scaling multimodal models, either personally or professionally.</li>\n<li>Experience in software development, with a focus on building end-to-end AI consumer products.</li>\n<li>Experience with modern Frontend and/or Backend frameworks.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Passion for learning new technologies and staying up to date with industry trends, best practices, and emerging technologies in web development and AI.</li>\n<li>Ability to work in a fast-paced environment, manage multiple priorities, and adapt to changing requirements and deadlines.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary and benefits package.</li>\n<li>Opportunity to work on cutting-edge AI projects and technologies.</li>\n<li>Collaborative and dynamic work environment.</li>\n<li>Professional development opportunities.</li>\n<li>Flexible working hours and 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_e96eb441-8d9","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-senior-software-engineer/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"Competitive salary and benefits package","x-skills-required":["Machine Learning frameworks","software development","Frontend and/or Backend frameworks"],"x-skills-preferred":["multimodal models","web development","AI"],"datePosted":"2026-03-06T07:27:08.028Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning frameworks, software development, Frontend and/or Backend frameworks, multimodal models, web development, AI"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_ff47f52d-9d5"},"title":"Member of Technical Staff, AI Multimodal","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Member of Technical Staff, AI Multimodal at their London 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 a Member of Technical Staff, AI Multimodal, you will be responsible for developing algorithms, designing model architectures, conducting experiments, championing measurement and evaluation, innovating datasets and data pipelines. You will improve training and deployment efficiency, paying careful attention to detail, persevering, and learning from everyone&#39;s attempts whether successful or not. You will follow a rigorous data-driven approach grounded in meticulous ablation studies and scientific analysis. You will innovate and iterate over ideas, prototypes, and product. 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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 a Member of Technical Staff, Multimodal Safety, you will work to develop and implement cutting-edge safety methodologies for post-training multimodal large language models to be served to millions of users through Copilot every day. We work on the bleeding edge and leverage the most powerful pretrained models and algorithms, making it critical that we ensure our AI systems behave safely and align with organizational values.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Leverage expertise in multimodal safety to uncover potential risks and develop novel mitigation strategies, including alignment techniques and robustness improvements for multimodal large language models.</li>\n<li>Create and implement comprehensive evaluation frameworks and red-teaming methodologies to assess model safety across diverse scenarios, edge cases, and potential failure modes.</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 4+ 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>Proven expertise in multimodal LLM safety with experience in diffusion models and generative image/video/audio.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Track record building evaluation frameworks, automated red-teaming, and reusable guardrail systems for safety at scale.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Software Engineering IC4 – The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year.</li>\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</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_b8f14b8a-01e","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/member-of-technical-staff-multimodal-safety-mai-super-intelligence-team/","x-work-arrangement":"hybrid","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"USD $119,800 – $234,700 per year","x-skills-required":["multimodal safety","diffusion models","generative image/video/audio","evaluation frameworks","red-teaming methodologies"],"x-skills-preferred":["alignment techniques","robustness improvements","guardrail systems"],"datePosted":"2026-03-06T07:26:54.638Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"multimodal safety, diffusion models, generative image/video/audio, evaluation frameworks, red-teaming methodologies, alignment techniques, robustness improvements, guardrail systems","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_9e63acec-fe1"},"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 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 a Senior Applied Scientist, you&#39;ll lead the science behind Discover&#39;s ranking and content-quality stack, combining LLMs, multimodal models, and large-scale recommender systems to drive measurable gains in engagement, satisfaction, and trust. 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This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising AI-powered quality understanding and recommendation systems.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Principal Applied Scientist, you&#39;ll lead the science behind Discover&#39;s ranking and content-quality stack, combining LLMs, multimodal models, and large-scale recommender systems to drive measurable gains in engagement, satisfaction, and trust. You will set technical direction, mentor a high-caliber science cohort, and partner closely with engineering, PM, UXR, and policy to ship end-to-end outcomes.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Lead content-quality understanding at scale.</li>\n<li>Advance the recommendation &amp; ranking stack.</li>\n<li>Own evaluation and experimentation.</li>\n<li>Champion safety &amp; trust.</li>\n<li>Scale E2E ML systems.</li>\n<li>Mentor &amp; influence.</li>\n<li>Stay close to users.</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>Expertise with LLMs (prompting, finetuning, RAG), multimodal modeling, and retrieval-augmented recommendation; familiarity with counterfactual learning and multi-objective optimization.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Demonstrated ability to lead cross-disciplinary efforts (PM, ENG, UXR, editorial/policy) from idea to shipped impact; mentoring scientists and setting technical vision.</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_6b47ab3c-965","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-5/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"Competitive salary and benefits package","x-skills-required":["LLMs","multimodal modeling","retrieval-augmented recommendation","counterfactual learning","multi-objective optimization"],"x-skills-preferred":["Python","Azure ML","Kusto","Synapse","Azure AI Foundry"],"datePosted":"2026-03-06T07:25:18.741Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"LLMs, multimodal modeling, retrieval-augmented recommendation, counterfactual learning, multi-objective optimization, Python, Azure ML, Kusto, Synapse, Azure AI Foundry"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_aa8c53c2-ca3"},"title":"Search Machine Learning Research Engineer","description":"<p>Perplexity is seeking an experienced Senior Machine Learning Engineer to help build the next generation of advanced search technologies, with a focus on retrieval and ranking. The successful candidate will be responsible for pushing search quality forward through models, data, tools, or any other leverage available.</p>\n<p><strong>What you&#39;ll do</strong></p>\n<p>The Senior Machine Learning Engineer will be responsible for architecting and building core components of the search platform and model stack. 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