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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 range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_465e2cfb-ddc","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4628044005","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$264,800-$331,000 USD","x-skills-required":["large language model","NLP","Transformer modeling","evaluation methodologies","metrics","benchmarks","instruction following","factuality","robustness","fairness"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:59:31.100Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; Seattle, WA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"large language model, NLP, Transformer modeling, evaluation methodologies, metrics, benchmarks, instruction following, factuality, robustness, fairness","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":264800,"maxValue":331000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d9da00f5-0b0"},"title":"Transformative AI Research Economist, Economic Research","description":"<p>As a Transformative AI Research Economist at Anthropic, you will build macroeconomic models of AI that could be genuinely transformative and develop the scenario-based forecasting tools that let us reason quantitatively about economic trajectories with no historical precedent.\\n\\nYou will ground projections in microeconomic signals from the Anthropic Economic Index , usage patterns across millions of real-world AI interactions, surfaced through privacy-preserving measurement , so that scenario forecasts are disciplined by what we actually observe about task transformation and productivity.\\n\\nOur team combines rigorous empirical methods with novel measurement approaches. We&#39;re building first-of-its-kind datasets tracking AI&#39;s impact on labor markets, productivity, and economic transformation.\\n\\nResponsibilities:\\n\\n<em> Build macroeconomic models of transformative AI spanning growth, labor markets, and income distribution\\n</em> Develop and maintain scenario-based forecasting tools; publish forecasts for GDP, productivity, and unemployment under a range of AI-capability trajectories\\n<em> Ground macroeconomic projections in microeconomic data from the Anthropic Economic Index, constraining theory with observed patterns of adoption and task transformation\\n</em> Analyze questions of income distribution and economic governance under transformative-AI scenarios\\n<em> Contribute to the development of AI-powered research tools for economics\\n</em> Contribute to Economic Index Reports and publish Research Briefs on first-order questions as they arise\\n<em> Build and maintain relationships with academic institutions, policy think tanks, and other research partners\\n</em> Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders\\n\\nYou May Be a Good Fit If You Have:\\n\\n<em> PhD in Economics, or an exceptional candidate close to completion\\n</em> Background in macroeconomics, growth theory, or public finance ideally with exposure to task-based frameworks and labor economics\\n<em> A research record that engages seriously with the possibility of transformative AI , you treat the scenarios in this posting as live questions worth modeling rigorously, not speculation to be hedged against\\n</em> Relevant experience in some of:\\n\\n<em> Macroeconomic modeling and structural estimation\\n</em> Scenario-based and time-series forecasting\\n<em> Task-based approaches to technological change\\n</em> Computational methods, agent-based modeling, or large-scale simulation\\n<em> Income distribution and inequality\\n</em> Using large language models in the research workflow\\n<em> Technical skills including:\\n\\n</em> Proficiency in Python, Julia, or similar for computational economics\\n<em> Facility with AI coding agents as part of a research workflow\\n</em> Comfort learning new technical tools and frameworks\\n<em> Demonstrated ability to:\\n\\n</em> Lead research projects from conception to publication\\n<em> Ship on tight timelines and revise in public as new data arrives\\n</em> Communicate technical findings to diverse audiences\\n<em> Strong interest in ensuring AI development benefits humanity\\n\\nSome Examples of Our Recent Work:\\n\\n</em> Labor market impacts of AI: A new measure and early evidence\\n<em> Anthropic Economic Index Report: Economic Primitives\\n</em> Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption\\n<em> Estimating AI productivity gains from Claude conversations\\n</em> The Anthropic Economic Index\\n\\nAdditional Information:\\n\\nFor this role, we&#39;re looking for candidates who combine rigorous macroeconomic theory with computational fluency, and who are willing to model economic scenarios that fall outside the profession&#39;s usual range. The ideal candidate works at the intersection of growth theory, forecasting, and frontier AI.\\n\\nDeadline to apply: None. Applications are reviewed on a rolling basis\\n\\nThe annual compensation range for this role is listed below.\\n\\nFor sales roles, the range provided is the role’s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\\n\\nAnnual Salary: $300,000-$405,000 USD</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_d9da00f5-0b0","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5149802008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$300,000-$405,000 USD","x-skills-required":["Python","Julia","macroeconomic modeling","structural estimation","scenario-based forecasting","time-series forecasting","task-based approaches to technological change","computational methods","agent-based modeling","large-scale simulation","income distribution","inequality","large language models"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:59:25.435Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Julia, macroeconomic modeling, structural estimation, scenario-based forecasting, time-series forecasting, task-based approaches to technological change, computational methods, agent-based modeling, large-scale simulation, income distribution, inequality, large language models","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":300000,"maxValue":405000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_539e2a23-ddf"},"title":"Tech Lead Manager- MLRE, ML Systems","description":"<p>You will lead the development of our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline.</p>\n<p>You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. 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Experience supporting and leading a team of research scientists and research engineers is also required.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_60a7e1e6-b51","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4304790005","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$264,800-$331,000 USD","x-skills-required":["large language model","NLP","Transformer modeling","research and engineering development","team leadership","cross-functional collaboration","evaluation methodologies","metrics and benchmarks","scalable and reproducible evaluation pipelines","modern ML frameworks"],"x-skills-preferred":["published research in top-tier AI conferences","open-source benchmarking initiatives","customer-facing role"],"datePosted":"2026-04-18T15:59:10.794Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; Seattle, WA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"large language model, NLP, Transformer modeling, research and engineering development, team leadership, cross-functional collaboration, evaluation methodologies, metrics and benchmarks, scalable and reproducible evaluation pipelines, modern ML frameworks, published research in top-tier AI conferences, open-source benchmarking initiatives, customer-facing role","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":264800,"maxValue":331000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_fb1f459e-b3a"},"title":"Machine Learning Research Scientist / Engineer, Reasoning","description":"<p>About Scale</p>\n<p>At Scale, our mission is to accelerate the development of AI applications. We&#39;re looking for a Machine Learning Research Scientist/Engineer to join our team and help us shape the future of AI.</p>\n<p>This role operates at the forefront of AI research and real-world implementation, with a strong focus on reasoning within large language models (LLMs). You will study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents. You will play a key role in shaping Scale&#39;s data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning.</p>\n<p>Success in this role requires a deep understanding of LLMs, planning algorithms, and novel approaches to agentic reasoning, as well as creativity in tackling challenges related to data generation, model interaction, and evaluation. You will contribute to impactful research on language model reasoning, collaborate with external researchers, and work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions.</p>\n<p>Responsibilities</p>\n<ul>\n<li>Study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents</li>\n<li>Shape Scale&#39;s data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning</li>\n<li>Contribute to impactful research on language model reasoning</li>\n<li>Collaborate with external researchers</li>\n<li>Work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions</li>\n</ul>\n<p>Requirements</p>\n<ul>\n<li>Practical experience working with LLMs, with proficiency in frameworks like PyTorch, JAX, or TensorFlow</li>\n<li>A track record of published research in top ML and NLP venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, CoLLM, etc.)</li>\n<li>At least three years of experience solving complex ML challenges, either in a research setting or product development, particularly in areas related to LLM capabilities and reasoning</li>\n<li>Strong written and verbal communication skills, along with the ability to work effectively across teams</li>\n</ul>\n<p>Nice to Have</p>\n<ul>\n<li>Hands-on experience fine-tuning open-source LLMs or leading bespoke LLM fine-tuning projects using PyTorch/JAX</li>\n<li>Research and practical experience in building applications and evaluations related to LLM-based agents, including tool-use, text-to-SQL, browser agents, coding agents, and GUI agents</li>\n<li>Experience with agent frameworks such as OpenHands, Swarm, LangGraph, or similar</li>\n<li>Familiarity with advanced agentic reasoning techniques such as STaR and PLANSEARCH</li>\n<li>Proficiency in cloud-based ML development, with experience in AWS or GCP environments</li>\n</ul>\n<p>Benefits</p>\n<ul>\n<li>Comprehensive health, dental and vision coverage</li>\n<li>Retirement benefits</li>\n<li>A learning and development stipend</li>\n<li>Generous PTO</li>\n<li>Commuter stipend</li>\n</ul>\n<p>Salary Range</p>\n<p>$252,000-$315,000 USD</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_fb1f459e-b3a","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale AI","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4605596005","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$252,000-$315,000 USD","x-skills-required":["PyTorch","JAX","TensorFlow","Large Language Models (LLMs)","Planning Algorithms","Agentic Reasoning","Data Generation","Model Interaction","Evaluation"],"x-skills-preferred":["Agent Frameworks","Cloud-Based ML Development","AWS","GCP","STaR","PLANSEARCH"],"datePosted":"2026-04-18T15:59:07.207Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; Seattle, WA; New York, NY"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"PyTorch, JAX, TensorFlow, Large Language Models (LLMs), Planning Algorithms, Agentic Reasoning, Data Generation, Model Interaction, Evaluation, Agent Frameworks, Cloud-Based ML Development, AWS, GCP, STaR, PLANSEARCH","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":252000,"maxValue":315000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b255adba-bf4"},"title":"Field Engineer, Public Sector","description":"<p>We&#39;re looking for a Field Engineer to join our Public Sector team. As a Field Engineer, you will be on the front lines of our field engineering efforts for our federal AI projects, working closely with our largest public sector customers to ensure seamless and optimized experiences with Scale&#39;s technology.</p>\n<p>Your primary responsibilities will include implementing end-to-end data integrations, syncing customer&#39;s data to Scale&#39;s platform and back, and working closely with our customer&#39;s engineering teams to optimize data pipelines. You will also design, develop and maintain playbooks, internal tools, Scale&#39;s documentation and SDKs to quickly get customers set up for long-term success.</p>\n<p>In addition, you will partner with Software Engineers and Operations to remove any technical hurdles customers may face, debug technical issues impacting delivery and own technical escalations coming from the customer. You will be accountable for the customer&#39;s technical experience throughout their time with Scale.</p>\n<p>The ideal candidate will have a track record of success as a hybrid customer-facing engineer or similar function, wearing multiple hats along the way. Prior technical hands-on experience working with clients in a pre or post-sales capacity to realize business goals is also required.</p>\n<p>We offer a competitive compensation package, including base salary, equity, and benefits. The base salary range for this full-time position is $190,000-$290,000 USD in San Francisco, New York, and Seattle, $170,000-$260,000 USD in Hawaii, Washington DC, Texas, and Colorado, and $140,000-$220,000 USD in St. Louis.</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_b255adba-bf4","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://www.scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4518690005","x-work-arrangement":"onsite","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$190,000-$290,000 USD in San Francisco, New York, and Seattle, $170,000-$260,000 USD in Hawaii, Washington DC, Texas, and Colorado, and $140,000-$220,000 USD in St. Louis","x-skills-required":["Python","JavaScript","API integrations","Large Language Models","2D Image Annotation","Container orchestration with Kubernetes","Helm charts for application deployment","Ansible or similar tools for automation"],"x-skills-preferred":["Experience in AI","Experience working in classified environments","Previous experience as a technical go-to-market resource","Understanding of DevSecOps principles"],"datePosted":"2026-04-18T15:58:59.499Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; New York, NY; Honolulu, Hawaii, St. Louis, MO; Washington, DC"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, JavaScript, API integrations, Large Language Models, 2D Image Annotation, Container orchestration with Kubernetes, Helm charts for application deployment, Ansible or similar tools for automation, Experience in AI, Experience working in classified environments, Previous experience as a technical go-to-market resource, Understanding of DevSecOps principles","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":140000,"maxValue":290000,"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_43334479-97e"},"title":"Sr Analytics Engineer - GTM Strategy and Operations","description":"<p>As a Senior Analytics Engineer, you will be a critical partner to the Global GTM Strategy &amp; Operations teams, providing the data, AI-driven insights, and infrastructure needed to drive efficiency and effectiveness across the organization.</p>\n<p>You will design, build, and maintain scalable data models, curated reporting tables, forecasts, and dashboards that support everyone from senior executives to individual contributors, empowering them to make informed decisions and spend more time driving customer outcomes.</p>\n<p>Working closely with cross-functional stakeholders,including Sales, Finance, Marketing, and other data teams,you will tackle complex data challenges by leveraging structured data, building AI-powered querying assistants, and using tools like Databricks Genie to improve data accessibility, streamline insights, and deliver actionable, reliable solutions across the business.</p>\n<p>You will also play a key role in advancing our newly created AI initiatives and semantic data curation efforts, helping to establish a strong foundation for advanced analytics, automation, and scalable business intelligence.</p>\n<p>The Impact You Will Have:</p>\n<ul>\n<li>Build: You will design and develop analytic tools, including a semantic layer for AI use cases, scalable data models, curated tables, and insightful analyses that empower thousands of field employees and leaders worldwide.</li>\n</ul>\n<ul>\n<li>Architect: You will both manage the requirements gathering and lead execution of strategic analytic projects.</li>\n</ul>\n<ul>\n<li>Scale: You will build and manage relationships with stakeholders across the company but primarily with the GTM strategy and operations team</li>\n</ul>\n<p>What we look for:</p>\n<ul>\n<li>You have 4+ years of experience working as an Analyst / Data Engineer / Analytics Engineer with B2B sales, marketing, or finance data (GTM experience highly preferred).</li>\n</ul>\n<ul>\n<li>You are data-savvy with 3+ years of SQL and 2+ years of Python experience. Familiarity with data ecosystems and BI tools (e.g., Databricks, PowerBI) is required.</li>\n</ul>\n<ul>\n<li>You have built for scale. You have experience building scalable and productionizable data models with best practices in mind.</li>\n</ul>\n<ul>\n<li>You integrate AI into your daily workflow. You have hands-on experience using large language model tools (such as Claude or similar) to accelerate analytics work , from drafting and debugging code to synthesizing requirements and generating documentation.</li>\n</ul>\n<ul>\n<li>You&#39;re comfortable evaluating AI-generated outputs critically and iterating quickly.</li>\n</ul>\n<ul>\n<li>You are passionate about applying AI to transform GTM teams. You bring experience in delivering AI-driven solutions and have the ability to design innovative use cases as well as structure data models and tables that are optimized for AI readiness.</li>\n</ul>\n<ul>\n<li>You excel in partnering with the business, understanding the impact of your work on GTM, and creating innovative solutions.</li>\n</ul>\n<ul>\n<li>You have a track record of cross-functional collaboration and strong stakeholder relationships.</li>\n</ul>\n<ul>\n<li>You excel in a collaborative environment. You translate team member needs into clear tasks and deliverables for contributors.</li>\n</ul>\n<ul>\n<li>You work through dependencies, bottlenecks, and tradeoffs with ease.</li>\n</ul>\n<ul>\n<li>You have a service-oriented mindset.</li>\n</ul>\n<ul>\n<li>You are curious, creative, and kind.</li>\n</ul>\n<p>Pay Range Transparency:</p>\n<p>Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.</p>\n<p>Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.</p>\n<p>Based on the factors above, Databricks anticipates utilizing the full width of the range.</p>\n<p>The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.</p>\n<p>For more information regarding which range your location is in visit our page here.</p>\n<p>Zone 1 Pay Range $133,000-$182,950 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_43334479-97e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Databricks","sameAs":"https://databricks.com","logo":"https://logos.yubhub.co/databricks.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/databricks/jobs/8479036002","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$133,000-$182,950 USD","x-skills-required":["SQL","Python","Databricks","PowerBI","Data Engineering","Analytics Engineering","AI","Machine Learning"],"x-skills-preferred":["Large Language Model Tools","Claude","Semantic Data Curation","Advanced Analytics","Automation","Scalable Business Intelligence"],"datePosted":"2026-04-18T15:58:18.439Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York; San Francisco, California"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"SQL, Python, Databricks, PowerBI, Data Engineering, Analytics Engineering, AI, Machine Learning, Large Language Model Tools, Claude, Semantic Data Curation, Advanced Analytics, Automation, Scalable Business Intelligence","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":133000,"maxValue":182950,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_675c7117-57f"},"title":"Strategic Solutions Engineer, East","description":"<p>As a Strategic Solutions Engineer, you&#39;ll be at the forefront of the AI transformation in customer experience. Partnering with Sales Directors, you&#39;ll serve as both a business consultant and technical expert,guiding prospective customers through the discovery, design, and validation of Cresta&#39;s AI-powered solutions.</p>\n<p>You&#39;ll connect deeply with customer stakeholders to understand their business goals, technical environments, and operational challenges, and architect intelligent solutions that combine the power of LLMs, SLMs, and real-time AI assistance. Your ability to translate both technical complexity and business impact will be critical to driving successful sales cycles and long-term customer outcomes.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Act as a consultative partner to customers,uncovering business objectives, technical environments, and operational challenges to map them to AI-driven solutions.</li>\n<li>Act as a consultative advisor to prospective customers, uncovering operational workflows and strategic goals to design solutions leveraging Cresta’s real-time AI capabilities, including virtual agents, agent assist, and conversation intelligence.</li>\n<li>Lead technical discovery sessions to understand customer systems, including contact center infrastructure, telephony and IVR architecture, and CRM/workforce management platforms.</li>\n<li>Qualify and translate customer requirements into robust, scalable Cresta configurations, ensuring tight alignment with business value and technical feasibility.</li>\n<li>Design and deliver compelling, tailored product demonstrations that highlight how Cresta’s AI-powered virtual agents, real-time coaching, and analytics can deliver measurable business outcomes.</li>\n<li>Own the technical design and delivery of proof-of-value (POV) engagements, including integrations, real-time coaching workflows, and virtual agent use cases.</li>\n<li>Run ROI workshops and build business case models that connect Cresta’s capabilities to quantifiable customer impact (e.g., cost reduction, efficiency, CSAT).</li>\n<li>Provide insights based on your experience with AI technologies, contact center transformation, and customer success strategies.</li>\n<li>Serve as a technical liaison between Sales, Product, and Engineering,providing feedback on platform capabilities, customer needs, and market trends in AI, NLP, and contact center transformation.</li>\n<li>Stay current on emerging technologies, including LLMs, SLMs, retrieval-augmented generation (RAG), speech recognition, and contact center AI platforms.</li>\n<li>Deliver persuasive, tailored product demonstrations that showcase how Cresta’s AI,built on a proprietary architecture using large and small language models,drives measurable ROI through automation, efficiency, and improved customer outcomes.</li>\n</ul>\n<p>Qualifications:</p>\n<ul>\n<li>7+ years of experience in customer-facing roles, including 1–3 years in pre-sales, solutions engineering, or consulting within the enterprise software or contact center industry.</li>\n<li>Deep knowledge of contact center solutions, including telephony architecture (SIP, SBCs, ACDs, IVRs) and CCaaS platforms (e.g., Genesys, NICE, Five9, Amazon Connect).</li>\n<li>Strong understanding of AI/ML technologies, especially large language models (LLMs), small language models (SLMs), and how they are applied in conversational AI and agent augmentation.</li>\n<li>Experience with real-time systems, CRM tools (e.g., Salesforce), analytics platforms, and SaaS solution architecture.</li>\n<li>Ability to design and communicate complex solutions clearly to both technical and business audiences.</li>\n<li>Consultative mindset with a proven track record of leading strategic conversations, influencing stakeholders, and tailoring solutions to business goals.</li>\n<li>Fast learner and self-starter who thrives in high-growth, high-collaboration environments.</li>\n<li>Enthusiastic about Cresta’s mission and motivated to help customers unlock value from AI.</li>\n</ul>\n<p>Perks &amp; Benefits:</p>\n<p>We offer a comprehensive and people-first benefits package to support you at work and in life:</p>\n<ul>\n<li>Comprehensive medical, dental, and vision coverage with plans to fit you and your family</li>\n<li>Flexible PTO to take the time you need, when you need it</li>\n<li>Paid parental leave for all new parents welcoming a new child</li>\n<li>Retirement savings plan to help you plan for the future</li>\n<li>Remote work setup budget to help you create a productive home office</li>\n<li>Monthly wellness and communication stipend to keep you connected and balanced</li>\n<li>In-office meal program and commuter benefits provided for onsite employees</li>\n</ul>\n<p>Compensation at Cresta:</p>\n<p>Cresta’s approach to compensation is simple: recognize impact, reward excellence, and invest in our people. We offer competitive, location-based pay that reflects the market and what each individual brings to the table. The posted base salary range represents what we expect to pay for this role in a given location. Final offers are shaped by factors like experience, skills, education, and geography. In addition to base pay, total compensation includes equity and a comprehensive benefits package for you and your family. This role is variable target compensation eligible. There is potential to exceed target earnings when goals are surpassed.</p>\n<p>Base Salary Range: $180,000–$205,000 + variable &amp; Offers Equity</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_675c7117-57f","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Cresta","sameAs":"https://www.cresta.ai/","logo":"https://logos.yubhub.co/cresta.ai.png"},"x-apply-url":"https://job-boards.greenhouse.io/cresta/jobs/4985070008","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$180,000–$205,000 + variable & Offers Equity","x-skills-required":["contact center solutions","telephony architecture","CCaaS platforms","AI/ML technologies","large language models","small language models","conversational AI","agent augmentation","real-time systems","CRM tools","analytics platforms","SaaS solution architecture"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:57:54.328Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"United States (Remote)"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"contact center solutions, telephony architecture, CCaaS platforms, AI/ML technologies, large language models, small language models, conversational AI, agent augmentation, real-time systems, CRM tools, analytics platforms, SaaS solution architecture","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":180000,"maxValue":205000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_bfddfcc3-e38"},"title":"Senior Software Engineer, Public Sector","description":"<p>As a Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders.</p>\n<p>You will:</p>\n<p>Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers. Manage the full lifecycle of feature development from requirement definition to deployment on classified networks. Direct the orchestration of asynchronous agent fleets to meet mission requirements. Lead customer engagements to translate mission needs into technical requirements. Own the communication with stakeholders to ensure implementation meets defined acceptance criteria. Conduct technical reviews and identify risks within machine learning infrastructure and model serving. Drive the platform roadmap by providing technical specifications for Federal product offerings.</p>\n<p>Ideally you will have:</p>\n<p>Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles AI Application Integration: Familiarity with integrating Large Language Models (LLMs) and building agentic workflows. Understanding of prompt engineering, retrieval-augmented generation (RAG), and agent orchestration is beneficial. Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to defining and evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering</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_bfddfcc3-e38","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://www.scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4674911005","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$216,000-$311,000 USD (San Francisco, New York, Seattle) $194,400-$279,000 USD (Hawaii, Washington DC, Texas, Colorado) $162,400-$233,000 USD (St. Louis)","x-skills-required":["Full Stack Development","Cloud-Native Technologies","Data Engineering","AI Application Integration","Problem Solving","Collaboration and Communication","Adaptability and Learning Agility"],"x-skills-preferred":["Docker","Kubernetes","AWS","Azure","GCP","ETL","data modeling","data warehousing","data governance","Large Language Models","prompt engineering","retrieval-augmented generation","agent orchestration"],"datePosted":"2026-04-18T15:57:07.621Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; St. Louis, MO; New York, NY; Washington, DC"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Full Stack Development, Cloud-Native Technologies, Data Engineering, AI Application Integration, Problem Solving, Collaboration and Communication, Adaptability and Learning Agility, Docker, Kubernetes, AWS, Azure, GCP, ETL, data modeling, data warehousing, data governance, Large Language Models, prompt engineering, retrieval-augmented generation, agent orchestration","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":162400,"maxValue":311000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6639ec6c-3f8"},"title":"Strategic Solutions Engineer, West","description":"<p>As a Strategic Solutions Engineer, you&#39;ll be at the forefront of the AI transformation in customer experience. You&#39;ll partner with Sales Directors to guide prospective customers through the discovery, design, and validation of Cresta&#39;s AI-powered solutions.</p>\n<p>Your ability to translate both technical complexity and business impact will be critical to driving successful sales cycles and long-term customer outcomes.</p>\n<p>Responsibilities: Act as a consultative partner to customers,uncovering business objectives, technical environments, and operational challenges to map them to AI-driven solutions. Act as a consultative advisor to prospective customers, uncovering operational workflows and strategic goals to design solutions leveraging Cresta&#39;s real-time AI capabilities, including virtual agents, agent assist, and conversation intelligence. Lead technical discovery sessions to understand customer systems, including contact center infrastructure, telephony and IVR architecture, and CRM/workforce management platforms. Qualify and translate customer requirements into robust, scalable Cresta configurations, ensuring tight alignment with business value and technical feasibility. Design and deliver compelling, tailored product demonstrations that highlight how Cresta&#39;s AI-powered virtual agents, real-time coaching, and analytics can deliver measurable business outcomes. Own the technical design and delivery of proof-of-value (POV) engagements, including integrations, real-time coaching workflows, and virtual agent use cases. Run ROI workshops and build business case models that connect Cresta&#39;s capabilities to quantifiable customer impact (e.g., cost reduction, efficiency, CSAT). Provide insights based on your experience with AI technologies, contact center transformation, and customer success strategies. Serve as a technical liaison between Sales, Product, and Engineering,providing feedback on platform capabilities, customer needs, and market trends in AI, NLP, and contact center transformation. Stay current on emerging technologies, including LLMs, SLMs, retrieval-augmented generation (RAG), speech recognition, and contact center AI platforms. 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You will employ your excellent communication skills to explain and demonstrate complex solutions persuasively to technical and non-technical audiences alike.</p>\n<p>You will play a critical role in identifying opportunities to accelerate indirect revenue, enable partner AI practices, and execute on long-term international GTM strategy, while maintaining our best-in-class safety standards.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Team Leadership &amp; Development: Manage and mentor a team of Applied AI, Partner Solutions Architects, providing both technical guidance and career development. Set goals and reviews for your team, promoting growth and output</li>\n</ul>\n<ul>\n<li>Strategic Technical Partnership: Serve as the senior technical thought partner to the Anthropic international GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities across international markets</li>\n</ul>\n<ul>\n<li>Partner Ecosystem Enablement: Embed your team with GSI and cloud partner technical teams to enable their AI practices, support troubleshooting, evangelize Anthropic in their developer communities, and serve as an escalation point for complex technical issues</li>\n</ul>\n<ul>\n<li>Joint Solution Development: Lead your team in collaborating with partners to identify high-value industry-specific GenAI applications, develop joint solutions, and codify reference architectures / best practices to accelerate time to deployment across international markets</li>\n</ul>\n<ul>\n<li>Customer Deal Support: Own the technical portions of partner-led pre-sales engagements, ensuring your team intervenes directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance</li>\n</ul>\n<ul>\n<li>Partner Ecosystem &amp; Events: Represent Anthropic at international partner events such as GSI customer workshops, AWS summits, and industry conferences. Lead or support partner-specific developer events, hackathons, and technical enablement sessions</li>\n</ul>\n<ul>\n<li>Cross-Functional Collaboration: Drive collaboration from cross-functional teams to influence and unify stakeholders at all levels of the organization to drive business outcomes. Partner closely with your aligned GTM leadership to co-build international partner strategies</li>\n</ul>\n<ul>\n<li>Product Feedback: Validate and gather feedback on Anthropic&#39;s products and offerings, especially as they relate to international partner use cases and deployment patterns, and deliver this feedback to relevant Anthropic teams to inform product roadmap and partner strategy</li>\n</ul>\n<ul>\n<li>Thought Leadership: Contribute to thought leadership through conference presentations, webinars, and technical content creation focused on the international partner ecosystem</li>\n</ul>\n<p>You may be a good fit if you:</p>\n<ul>\n<li>7+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager</li>\n</ul>\n<ul>\n<li>5+ years of technical go-to-market management experience, specifically managing pre-sales or partner-facing technical teams across EMEA, APAC, and other international regions.</li>\n</ul>\n<ul>\n<li>Track record of successfully building and scaling partnerships with GSIs (e.g., Accenture, Deloitte, WPP, TCS, Infosys) and/or cloud providers (AWS, GCP) to solve complex technical challenges across international markets</li>\n</ul>\n<ul>\n<li>Experience with the unique dynamics of partner-led selling and delivery, including indirect revenue models and partner enablement at scale</li>\n</ul>\n<ul>\n<li>Deep technical proficiency with enterprise AI deployments, API integrations, and production LLM use cases</li>\n</ul>\n<ul>\n<li>Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders including C-suite executives, engineering &amp; 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As a member of our Safeguards team, you will be responsible for designing and overseeing the execution of capability evaluations to assess the cyber-relevant capabilities of new models. You will also create comprehensive cyber threat models, including attack vectors, exploit chains, precursor identification, and weaponization techniques.</p>\n<p>This is a unique opportunity to shape how frontier AI models handle dual-use cybersecurity knowledge,balancing the tremendous potential of AI to advance legitimate security research and defensive capabilities while preventing misuse by malicious actors.</p>\n<p>In this role, you will lead and grow a team of technical specialists focused on cyber threat modeling and evaluation frameworks. You will serve as the primary domain expert on cyber harms, advising cross-functional teams on threat landscapes and mitigation strategies.</p>\n<p>You will collaborate closely with internal and external threat modeling experts to develop training data for safety systems, and with ML engineers to train these systems, optimizing for both robustness against adversarial attacks and low false-positive rates for legitimate security researchers.</p>\n<p>You will also analyze safety system performance in traffic, identifying gaps and proposing improvements. You will conduct regular reviews of existing policies and enforcement systems to identify and address gaps and ambiguities related to cybersecurity risks.</p>\n<p>You will develop rigorous stress-testing of safeguards against evolving cyber threats and product surfaces. You will partner with Research, Product, Policy, Security Team, and Frontier Red Team to ensure cybersecurity safety is embedded throughout the model development lifecycle.</p>\n<p>You will translate cybersecurity domain knowledge into actionable safety requirements and clearly articulated policies. You will contribute to external communications, including model cards, blog posts, and policy documents related to cybersecurity safety.</p>\n<p>You will monitor emerging technologies and threat landscapes for their potential to contribute to new risks and mitigation strategies, and strategically address these.</p>\n<p>You will mentor and develop team members, fostering a culture of technical excellence and responsible AI development.</p>\n<p>To be successful in this role, you will need to have:</p>\n<ul>\n<li>An M.S. or PhD in Computer Science, Cybersecurity, or a related technical field, OR equivalent professional experience in offensive or defensive cybersecurity</li>\n<li>5+ years of hands-on experience in cybersecurity, with deep expertise in areas such as vulnerability research, exploit development, network security, malware analysis, or penetration testing</li>\n<li>2+ years of experience managing technical teams or leading complex technical projects with multiple stakeholders</li>\n<li>Experience in scientific computing and data analysis, with proficiency in programming (Python preferred)</li>\n<li>Deep expertise in modern cybersecurity, including both offensive techniques (vulnerability research, exploit development, penetration testing, malware analysis) and defensive measures (detection, monitoring, incident response)</li>\n<li>Demonstrated ability to create threat models and translate technical cyber risks into policy frameworks</li>\n<li>Familiarity with responsible disclosure practices, vulnerability coordination, and cybersecurity frameworks (e.g., MITRE ATT&amp;CK, NIST Cybersecurity Framework, CWE/CVE systems)</li>\n<li>Strong analytical and writing skills, with the ability to navigate ambiguity and explain complex technical concepts to non-technical stakeholders</li>\n<li>Experience developing policies or guidelines at scale, balancing safety concerns with enabling legitimate use cases</li>\n<li>A passion for learning new skills and an ability to rapidly adapt to changing techniques and technologies</li>\n<li>Comfort working in a fast-paced environment where priorities may shift as AI capabilities evolve</li>\n<li>Track record of translating specialized technical knowledge into actionable safety policies or enforcement guidelines</li>\n</ul>\n<p>Preferred qualifications include:</p>\n<ul>\n<li>Background in AI/ML systems, particularly experience with large language models</li>\n<li>Experience developing ML-based security systems or adversarial ML research</li>\n<li>Experience working with defense, intelligence, or security organizations (e.g., NSA, CISA, national labs, security contractors)</li>\n<li>Published security research, disclosed vulnerabilities, or participated in bug bounty programs</li>\n<li>Understanding of Trust &amp; Safety operations and content moderation at scale</li>\n<li>Certifications such as OSCP, OSCE, GXPN, or equivalent demonstrating technical depth</li>\n<li>Understanding of dual-use security research concerns and ethical considerations in AI safety</li>\n</ul>\n<p>The annual compensation range for this role is $320,000-$405,000 USD.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_7cc85573-4a2","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.co/","logo":"https://logos.yubhub.co/anthropic.co.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5066981008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$320,000-$405,000 USD","x-skills-required":["Cybersecurity","Vulnerability research","Exploit development","Network security","Malware analysis","Penetration testing","Detection","Monitoring","Incident response","Scientific computing","Data analysis","Programming (Python)","Responsible disclosure practices","Vulnerability coordination","Cybersecurity frameworks (MITRE ATT&CK, NIST Cybersecurity Framework, CWE/CVE systems)"],"x-skills-preferred":["AI/ML systems","Large language models","ML-based security systems","Adversarial ML research","Defense, intelligence, or security organizations","Published security research","Disclosed vulnerabilities","Bug bounty programs","Trust & Safety operations","Content moderation at scale","Certifications (OSCP, OSCE, GXPN)"],"datePosted":"2026-04-18T15:56:47.739Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote-Friendly (Travel-Required) | San Francisco, CA | Washington, DC"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Cybersecurity, Vulnerability research, Exploit development, Network security, Malware analysis, Penetration testing, Detection, Monitoring, Incident response, Scientific computing, Data analysis, Programming (Python), Responsible disclosure practices, Vulnerability coordination, Cybersecurity frameworks (MITRE ATT&CK, NIST Cybersecurity Framework, CWE/CVE systems), AI/ML systems, Large language models, ML-based security systems, Adversarial ML research, Defense, intelligence, or security organizations, Published security research, Disclosed vulnerabilities, Bug bounty programs, Trust & Safety operations, Content moderation at scale, Certifications (OSCP, OSCE, GXPN)","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_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. 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You will also raise the AI/ML skillset within the organization, which requires a passion for teaching and mentoring.</p>\n<p>To be successful in this role, you will need 12+ years of software engineering experience, with 2+ years of experience in a Principal or Senior Staff Engineer role having ownership responsibility over large-scale software systems. You should have a background in the design and development of scalable AI and ML systems and services, and a deep passion for building ML-powered products.</p>\n<p>As a Senior Staff Machine Learning Engineer, you will be an inspiring colleague, a coach, and mentor with experience owning and fostering engineering maturity in multiple organizations. You will be a builder, and implementer, who seeks out high-impact work, and who is proactive, curious, and an excellent communicator.</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_8b04e835-d14","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Airbnb","sameAs":"https://www.airbnb.com/","logo":"https://logos.yubhub.co/airbnb.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/airbnb/jobs/7005605","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$244,000-$305,000 USD","x-skills-required":["Machine Learning","Artificial Intelligence","Large Language Models","Recommendation Engines","Ranking Systems","Intent Detection Models"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:53:43.542Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - USA"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, Artificial Intelligence, Large Language Models, Recommendation Engines, Ranking Systems, Intent Detection Models","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":244000,"maxValue":305000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_01819c10-867"},"title":"PhD Machine Learning Engineer, Intern","description":"<p><strong>Job Description</strong></p>\n<p>We&#39;re excited to offer PhD machine learning engineering internships for the summer of 2026. 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You will work with data systems from across Anthropic, including our research tools for privacy-preserving analysis.\\n\\nThe Economic Research team at Anthropic studies the economic implications of AI on individual, firm, and economy-wide outcomes. We build scalable systems to monitor AI usage patterns and directly measure the impact of AI adoption on real-world outcomes. We publish research and data that is clear-eyed about the economic effects of AI to help policymakers, businesses, and the public understand and navigate the transition to powerful AI.\\n\\nIn this role, you will work closely with teams across Anthropic,including Data Science and Analytics, Data Infrastructure, Societal Impacts, and Public Policy,to build scalable and robust data systems that support high-leverage, high-impact research. Strong candidates will have a track record building data processing pipelines, architecting &amp; implementing high-quality internal infrastructure, working in a fast-paced startup environment, navigating ambiguity, and demonstrating an eagerness to develop their own research &amp; technical skills.\\n\\nResponsibilities:\\n\\n<em> Build and maintain data pipelines that process large scale Claude usage logs into canonical, reusable datasets while maintaining user privacy.\\n</em> Expand privacy-preserving tools to enable new analytic functionality to support research needs.\\n<em> Design and implement novel data systems leveraging language models (e.g., CLIO) where traditional software engineering patterns don&#39;t yet exist.\\n</em> Develop and maintain data pipelines that are interoperable across data sources (including ingesting external data) and are designed to support economic analysis.\\n<em> Contribute to the strategic development of the economic research data foundations roadmap\\n</em> Ensure data reliability, integrity, and privacy compliance across all economic research data infrastructure\\n<em> Lead technical design discussions to ensure our infrastructure can support both current needs and future research directions\\n</em> Create documentation and best practices that enable self-serve data access for researchers while maintaining security and governance standards.\\n<em> Partner closely with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic’s safety mission\\n\\nYou might be a good fit if you have:\\n\\n</em> Experience working with Research Scientists and Economists on ambiguous AI and economic projects\\n<em> Experience with building and maintaining data infrastructure, large datasets, and internal tools in production environments.\\n</em> Experience with cloud infrastructure platforms such as AWS or GCP.\\n<em> Take pride in writing clean, well-documented code in Python that others can build upon\\n</em> Are comfortable making technical decisions with incomplete information while maintaining high engineering standards\\n<em> Are comfortable getting up-to-speed quickly on unfamiliar codebases, and can work well with other engineers with different backgrounds across the organization\\n</em> Have a track record of using technical infrastructure to interface effectively with machine learning models\\n<em> Have experience deriving insights from imperfect data streams\\n</em> Have experience building systems and products on top of LLMs\\n<em> Have experience incubating and maturing tooling platforms used by a wide variety of stakeholders\\n</em> A passion for Anthropic&#39;s mission of building helpful, honest, and harmless AI and understanding its economic implications.\\n<em> A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end, even if it requires going outside the original job description.\\n</em> Strong communication skills to collaborate effectively with economists, researchers, and cross-functional partners who may have varying levels of technical expertise.\\n\\nStrong candidates may have:\\n\\n<em> Background in econometrics, statistics, or quantitative social science research\\n</em> Experience building data infrastructure and data foundations for research\\n<em> Familiarity with large language models, AI systems, or ML research workflows\\n</em> Prior work on projects related to labor economics, technology adoption, or economic measurement\\n\\nSome Examples of Our Recent Work\\n\\n<em> Anthropic Economic Index Report: Economic Primitives\\n</em> Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption\\n<em> Estimating AI productivity gains from Claude conversations\\n</em> The Anthropic Economic Index\\n\\nDeadline to apply: None. Applications are reviewed on a rolling basis\\n\\nThe annual compensation range for this role is listed below.\\n\\nFor sales roles, the range provided is the role’s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\\n\\nAnnual Salary: $300,000-$405,000 USD\\n\\nLogistics\\n\\nMinimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\\nRequired field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience\\nMinimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\\nLocation-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.\\nVisa 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.\\n\\nWe 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. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.\\n\\nYour 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.\\n\\nHow we&#39;re different\\n\\nWe 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 small\\n</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_4fde2d89-11c","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5071132008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$300,000-$405,000 USD","x-skills-required":["Python","Cloud infrastructure platforms (AWS or GCP)","Data infrastructure","Large datasets","Internal tools","Machine learning models","Econometrics","Statistics","Quantitative social science research","Large language models","AI systems","ML research workflows"],"x-skills-preferred":["Full-stack mindset","Strong communication skills","Ambiguity tolerance","Problem-solving skills","Collaboration skills"],"datePosted":"2026-04-18T15:52:18.267Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Cloud infrastructure platforms (AWS or GCP), Data infrastructure, Large datasets, Internal tools, Machine learning models, Econometrics, Statistics, Quantitative social science research, Large language models, AI systems, ML research workflows, Full-stack mindset, Strong communication skills, Ambiguity tolerance, Problem-solving skills, Collaboration skills","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":300000,"maxValue":405000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6556c9a6-357"},"title":"Senior Professional Services, Technical Architect - AI","description":"<p>As a Senior Professional Services Technical Architect, AI at GitLab, you&#39;ll be an embedded expert who helps customers move from ideas to production. 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You&#39;ll partner closely with Professional Services and Customer Success stakeholders, including Professional Services Engineers, Project Managers, Customer Success Managers, and Solution Architects.</p>\n<p>Some examples of our projects include leading customer discovery and defining a prioritized GitLab Duo Agent Platform use case roadmap tied to clear success criteria, designing and delivering production-ready GitLab Duo Agent Platform implementations, building rapid prototypes to demonstrate the art of the possible with agentic AI, and integrating the GitLab Duo Agent Platform with customer systems and workflows using GitLab APIs, pipeline configuration, and infrastructure as code.</p>\n<p>What you&#39;ll do:</p>\n<p>Conduct deep customer discovery to understand business goals, technical constraints, and organizational dynamics, and translate them into clear problem statements and a prioritized use case plan for GitLab Duo Agent Platform.</p>\n<p>Partner with customer stakeholders across engineering, security, compliance, and business teams to align on success criteria, milestones, and adoption strategy for AI workflows in production.</p>\n<p>Design, build, and deploy production-ready GitLab Duo Agent Platform solutions, including Custom Agents, Custom Flows, and CI/CD integrations that map to validated customer use cases.</p>\n<p>Embed with customer engineering teams to deliver hands-on implementations end-to-end, from prototype to production rollout, troubleshooting, and optimization.</p>\n<p>Configure and integrate platform foundations such as runners, network access, runtime sandboxing, GitLab APIs (REST and GraphQL), and AI governance controls (for example, role-based access control and model policies) to meet enterprise requirements.</p>\n<p>Measure and communicate impact using DORA (DevOps Research and Assessment) metrics, AI Impact Analytics, and Value Stream Analytics, and use those insights to guide iteration and expansion of successful use cases.</p>\n<p>Codify repeatable deployment patterns, reusable assets, and lessons learned, contributing back to GitLab through documentation, accelerators, and product feedback informed by field experience.</p>\n<p>Travel up to 50% for customer site engagements and company onsite events to support delivery, onboarding, and stakeholder alignment.</p>\n<p>What you&#39;ll bring:</p>\n<p>Demonstrated experience leading customer-facing technical engagements, from discovery through production rollout, with ownership of outcomes.</p>\n<p>Proficiency in Python, with experience building and operating production-grade applications and integrations.</p>\n<p>Experience delivering with GitLab CI/CD, including pipeline design, YAML configuration, and using GitLab APIs (REST and GraphQL).</p>\n<p>Hands-on experience with infrastructure as code (for example, Terraform or Ansible) and deploying solutions into enterprise environments.</p>\n<p>Working knowledge of large language model (LLM) capabilities and limitations, including prompt engineering and building agentic workflows (such as Custom Agents and Custom Flows).</p>\n<p>Experience with Docker, container orchestration concepts, and runner configuration in secure environments.</p>\n<p>Familiarity with DevSecOps practices, including security controls, access management, and compliance requirements that impact deployment design.</p>\n<p>Strong written and verbal communication skills, with the ability to partner closely with customer stakeholders and translate business goals into technical plans in a remote, asynchronous environment.</p>\n<p>About the team:</p>\n<p>GitLab&#39;s Professional Services organization within Customer Success helps customers get value from the GitLab Duo Agent Platform. 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You&#39;ll play a central role in how we integrate AI into CI/CD workflows. Your work will impact performance, reliability, and usability for people running millions of CI jobs, from small teams to the largest enterprises.</p>\n<p>In this role, you&#39;ll go beyond using AI tools and help define how we design, build, and iterate on AI-assisted and agentic CI experiences. You&#39;ll set standards for what good looks like across our AI agent portfolio, including how we measure success, how we instrument behavior in production, and how we account for large language model limitations. You&#39;ll also help responsibly integrate GitLab&#39;s Duo Agent Platform into CI workflows at scale, on a foundation that&#39;s fast, reliable, secure, and observable.</p>\n<p>We have ambitious goals for Agentic CI in FY27. As a Staff Engineer, you will:</p>\n<ul>\n<li>Partner with Engineering, Product, and UX leadership to pressure-test our priorities: where we can move faster, where we&#39;re missing data, and where there&#39;s whitespace to innovate. Part of this includes learning and growing with the Engineering team you will collaborate closely with.</li>\n</ul>\n<ul>\n<li>Define what success looks like across our agent portfolio and make sure we&#39;re tracking against it , not just shipping, but learning.</li>\n</ul>\n<ul>\n<li>Bring a sharp eye to the competitive landscape, helping us understand what it takes to keep GitLab CI best-in-class in an increasingly agentic world.</li>\n</ul>\n<p>Examples of Agentic CI work we have planned for the upcoming year:</p>\n<ul>\n<li>AI Pipeline Builder, the foundational CI agent that auto-creates pipelines for new projects and serves as the launchpad for onboarding new CI users.</li>\n</ul>\n<ul>\n<li>Automate the Fix a Failing Pipeline flow at scale – from dogfooding on internal GitLab projects through to safe, controlled rollout for customers, solving real infrastructure and scalability challenges.</li>\n</ul>\n<ul>\n<li>Build the instrumentation and observability layer that makes agentic CI trustworthy , trigger volume dashboards, retry rates, cost safeguards , so we can measure what&#39;s working, catch what isn&#39;t, and iterate with confidence.</li>\n</ul>\n<ul>\n<li>Harden the CI pipeline execution infrastructure that these agents depend on: database access patterns, background processing, and job orchestration built to handle the additional load that AI-driven automation introduces at enterprise scale.</li>\n</ul>\n<p>You&#39;ll shape and scale GitLab CI backend infrastructure to improve performance, reliability, and usability for users running jobs at high volume. You&#39;ll design and implement AI-powered features for Agentic CI, including agents, agentic flows, and LLM-backed tooling that integrates with GitLab&#39;s Duo Agent Platform. You&#39;ll define what success looks like for AI in CI before you build, including baselines, measurable outcomes, and clear signals that help the team learn and iterate. You&#39;ll build the instrumentation and observability needed to make AI-assisted CI trustworthy in production, including feature behavior metrics, dashboards, and safeguards. You&#39;ll own and drive measurable performance improvements across CI systems (for example, database access patterns, background processing, and job orchestration) by forming hypotheses, running experiments, and validating results with data. You&#39;ll write secure, well-tested, maintainable Ruby on Rails code in a large monolith, improving existing features while reducing technical debt and operational risk. You&#39;ll lead cross-functional technical work with Product, UX, and Infrastructure, influencing architecture and execution across the Verify stage. You&#39;ll share standards, patterns, and learnings with other engineers, raising the bar for responsible AI integration and evidence-driven engineering across CI.</p>\n<p>This role requires advanced proficiency with Ruby and Ruby on Rails, with experience building and maintaining reliable backend services in a large codebase. You should have strong PostgreSQL skills, including data modeling, query tuning, and scaling large tables through proactive performance investigation and remediation. You should have hands-on experience building, running, and debugging high-traffic production systems, ideally in CI, workflow orchestration, or adjacent infrastructure-heavy domains. You should have practical experience designing and shipping AI-powered backend features and integrations, including sound judgment about large language model limitations and responsible use in production. You should have a data-driven approach to engineering: defining hypotheses, establishing baseline metrics, instrumenting changes, and measuring outcomes against clear success criteria. You should have familiarity with observability patterns and tools (metrics, logging, tracing) to diagnose issues, improve reliability, and guide iteration. You should have strong backend architecture and delivery practices, including secure design, well-tested code, and strategies for safe rollouts and zero-downtime changes. You should have clear written and verbal communication skills, including writing technical proposals and documentation, and collaborating effectively in a remote, asynchronous, cross-functional environment.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_86696218-8f0","directApply":true,"hiringOrganization":{"@type":"Organization","name":"GitLab","sameAs":"https://about.gitlab.com/","logo":"https://logos.yubhub.co/about.gitlab.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/gitlab/jobs/8448283002","x-work-arrangement":"remote","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Ruby","Ruby on Rails","PostgreSQL","Data modeling","Query tuning","Scaling large tables","High-traffic production systems","CI","Workflow orchestration","Infrastructure-heavy domains","AI-powered backend features","Large language model limitations","Responsible use in production","Data-driven approach to engineering","Observability patterns","Metrics","Logging","Tracing","Backend architecture","Delivery practices","Secure design","Well-tested code","Safe rollouts","Zero-downtime changes"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:50:58.310Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote, APAC; Remote, Canada; Remote, Ireland; Remote, Netherlands; Remote, United Kingdom; Remote, US; Remote, US-Southeast"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Ruby, Ruby on Rails, PostgreSQL, Data modeling, Query tuning, Scaling large tables, High-traffic production systems, CI, Workflow orchestration, Infrastructure-heavy domains, AI-powered backend features, Large language model limitations, Responsible use in production, Data-driven approach to engineering, Observability patterns, Metrics, Logging, Tracing, Backend architecture, Delivery practices, Secure design, Well-tested code, Safe rollouts, Zero-downtime changes"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_062d8648-c7c"},"title":"Anthropic Fellows Program — ML Systems & Performance","description":"<p>About Anthropic\\n\\nAnthropic&#39;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole.\\n\\nApply using this link. The next cohort of Anthropic fellows starts on July 20, 2026. Apply by April 26, 2026 to be considered for this cohort. We will continue accepting applications for later cohorts on a rolling basis. In exceptional circumstances, we may be able to accommodate fellows starting outside of usual cohort timelines.\\n\\nThis page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.\\n\\nAnthropic Fellows Program overview\\n\\nThe Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience.\\n\\nFellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers.\\n\\nWe run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in July 2026 and beyond.\\n\\nWhat to expect\\n\\n- 4 months of full-time research \\n\\n- Direct mentorship from Anthropic researchers \\n\\n- Access to a shared workspace (in either Berkeley, California or London, UK)\\n\\n- Connection to the broader AI safety and security research community\\n\\n- Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country)\\n\\n- Funding for compute (~$15k/month) and other research expenses\\n\\nInterview process\\n\\nThe interview process will include an initial application &amp; reference check, technical assessments &amp; interviews, and a research discussion. \\n\\nCompensation\\n\\nThe expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension).\\n\\nFellows workstreams\\n\\nDue to the success of the Anthropic Fellows for AI Safety Research program, we are now expanding it across teams at Anthropic. We expect there to be significant overlap in the types of skills and responsibilities across the roles and will by default consider candidates for all the workstreams.\\n\\nSome of the workstreams may include unique assessment steps; we therefore ask you for workstream preferences in the application. You can see an overview of the current workstreams below:\\n\\n- AI Safety Fellows\\n\\n- AI Security Fellows\\n\\n- ML Systems &amp; Performance Fellows\\n\\n- Reinforcement Learning Fellows\\n\\n- Economics &amp; Societal Impacts Fellows\\n\\nAcross the workstreams, you may be a good fit if you:\\n\\n- Are motivated by making sure AI is safe and beneficial for society as a whole\\n\\n- Are excited to transition into empirical AI research and would be interested in a full-time role at Anthropic\\n\\n- Have a strong technical background in computer science, mathematics, or physics\\n\\n- Thrive in fast-paced, collaborative environments\\n\\n- Can implement ideas quickly and communicate clearly\\n\\nStrong candidates may also have:\\n\\n- Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity)\\n\\n- Experience in areas of research or engineering related to their workstream\\n\\nCandidates must be:\\n\\n- Fluent in Python programming\\n\\n- Available to work full-time on the Fellows program\\n\\nML Systems &amp; Performance Fellows\\n\\nMentors, research areas, &amp; past projects\\n\\nFellows will undergo a project selection &amp; mentor matching process. Potential mentors include:\\n\\n- Alwin Peng\\n\\n- Zygi Straznickas\\n\\nNote: You may research mentors&#39; prior work, but all applications must go through the official form, not the mentors.\\n\\nFor a past example of an engineering-heavy project, see:\\n\\n- AI agents find $4.6M in blockchain smart contract exploits\\n\\nProjects in this workstream may include:\\n\\n- Building a CPU simulator for accelerator workloads\\n\\n- Adding backends for different accelerators on an open source project\\n\\n- Building on demand infrastructure for other infrastructure heavy fellows projects \\n\\n- Building complex synthetic data or environment pipelines\\n\\nUnique candidate criteria\\n\\nYou might be a particularly great fit for this workstream if you:\\n\\n- Have strong software engineering skills with experience building complex ML systems\\n\\n- Can balance research exploration with engineering rigor and operational reliability\\n\\n- Enjoy collaborating across research and engineering disciplines\\n\\n- Are comfortable working with large-scale distributed systems and high-performance computing (e.g. in trading)\\n\\n- Have experience with training, fine-tuning, or evaluating large language models\\n\\n- Are adept at analyzing and debugging model training processes\\n\\nLogistics\\n\\nLogistics Requirements: To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program.\\n\\nWorkspace Locations: We have designated shared workspaces in London and Berkeley where fellows will work from and mentors will visit. We are also open to remote fellows in the UK, US, or Canada. We will ask you about your availability to work from Berkeley or London (full- or part-time) during the program.\\n\\nVisa Sponsorship: We are not currently able to sponsor visas for fellows. To participate in the Fellows program, you need to have or independently obtain full-time work authorization in the UK, the US, or Canada.\\n\\nProgram Duration: The program runs for 4 months, full-time. If you can&#39;t commit to the full duration, please still apply and note your constraints in the application. We review these requests on a case-by-case basis.\\n\\nPlease note: We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organizations.\\n\\nApplications and interviews are managed by Constellation, our official recruiting partner for this program. Constellation also runs the Berkeley workspace that hosts fellows. Clicking &quot;Apply here&quot; will redirect you to Constellation&#39;s application portal. You can expect to receive emails from Constellation with application updates.</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_062d8648-c7c","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5183051008","x-work-arrangement":"remote","x-experience-level":null,"x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python programming","AI research","Machine learning","Software engineering","Research and development","Collaboration","Communication","Problem-solving","Analytical thinking"],"x-skills-preferred":["Large language models","Distributed systems","High-performance computing","Trading","Synthetic data","Environment pipelines"],"datePosted":"2026-04-18T15:50:38.472Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK; Ontario, CAN; Remote-Friendly, United States; San Francisco, CA"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python programming, AI research, Machine learning, Software engineering, Research and development, Collaboration, Communication, Problem-solving, Analytical thinking, Large language models, Distributed systems, High-performance computing, Trading, Synthetic data, Environment pipelines"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_e0907526-c49"},"title":"Senior Privacy Architect Manager","description":"<p>We are looking for a Senior Manager, Privacy Architect to join our Privacy &amp; Data Security Team. As our growth accelerates through AI-powered personalization and innovative social features, privacy takes on new importance,fueling our ability to deliver magical, personalized experiences while ensuring our users feel safe, respected, and in control.</p>\n<p>The ideal candidate will have deep knowledge of current privacy and technology trends, with a strong passion for data governance/management and AI/ML. They will have demonstrated experience in ensuring privacy-by-design principles are applied throughout the design, construction, and operation of digital products and services at scale.</p>\n<p>Responsibilities include leading high-impact initiatives and defining technical requirements for compliance and the responsible use of technology at Airbnb. The candidate will work closely with the Chief Privacy Officer, Legal, and other Privacy &amp; Data Security Team members, as well as engineering and data science teams.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Collaborating with technical teams in the identification and effective management of company-wide risks to privacy and the responsible use of technology</li>\n<li>Leading definition and implementation of company-wide standards, practices, and patterns to protect and manage personal data in accordance with privacy and AI regulations</li>\n<li>Working with Legal, Data Science, Data Governance, and InfoSec to introduce Privacy by Design principles in company products and infrastructure</li>\n<li>Creating privacy training for technical roles, including data engineers, developers, and data scientists</li>\n</ul>\n<p>Requirements include:</p>\n<ul>\n<li>15+ years of total experience, with 5+ years of experience in technical program/project management or privacy engineering focused on building technology products and/or systems</li>\n<li>Deep understanding of large-scale, “Big Data” data stores and technologies</li>\n<li>Strong familiarity with the AI/ML development lifecycle: from data collection and curation, through model architecture selection, training, testing, A/B testing, and deployment</li>\n<li>Solid understanding of Large Language Models (LLMs), Generative AI and AI Agents, including compliance and responsible use challenges arising from their deployment in B2C services</li>\n<li>Strong familiarity with Privacy Enhancing Technologies (PETs), such as various types of encryption, de-identification methods (e.g., k-anonymity, differential privacy), and AI/ML interpretability techniques (e.g., SHAP, LIME)</li>\n</ul>\n<p>Preferred qualifications include:</p>\n<ul>\n<li>Professional certifications such as Certified Information Privacy Professional (CIPP), Certified Information Privacy Manager (CIPM), or AI Governance Professional (AIGP) or equivalent</li>\n<li>BA/BS and/or advanced degree in engineering, computer science, mathematics, statistics, physics, or a related field</li>\n<li>Experience with programming languages and tools commonly used in AI, such as R, Python and Github</li>\n</ul>\n<p>This position is US - Remote Eligible. 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Rather than delivering customer engagements directly, you&#39;ll design the offerings, frameworks, tooling requirements, and enablement that help field teams deliver those services effectively at scale.</p>\n<p>You&#39;ll also partner closely with the CX Engineering Platform team to help shape the CX Services roadmap for your area.</p>\n<p>This role is a strong fit for someone who brings an AI-forward working style and can apply it in practical ways, whether that means accelerating research, drafting requirements, building enablement, or improving how services are designed.</p>\n<p>You&#39;ll work across a broad set of stakeholders, from practitioners in the field to senior leadership, and help ensure GitLab services make it easier for customers to achieve meaningful outcomes with our platform.</p>\n<p>Some examples of our projects:</p>\n<ul>\n<li>Designing and evolving service offerings, delivery frameworks, and enablement for a specific product domain across the customer lifecycle</li>\n</ul>\n<ul>\n<li>Translating field feedback and customer needs into tooling requirements, service improvements, and scalable adoption paths for GitLab customers</li>\n</ul>\n<p><strong>What you’ll do</strong></p>\n<ul>\n<li>Own the end-to-end services portfolio for your assigned product area, including offer design, pricing, bill of materials standards, lifecycle management, field enablement, and sunset decisions.</li>\n</ul>\n<ul>\n<li>Map and continuously improve the customer journey for your product domain, defining how customers move across digital experiences, Customer Success tiers, Professional Services, and Education and Training.</li>\n</ul>\n<ul>\n<li>Define clear customer outcomes and value anchors for each offering so teams can communicate success consistently and track adoption, utilization, or expansion against agreed measures.</li>\n</ul>\n<ul>\n<li>Act as the product manager for tooling requirements related to your domain by partnering with the CX Engineering Platform team on requirements, backlog management, prototype reviews, and user acceptance testing to improve service delivery efficiency and user adoption.</li>\n</ul>\n<ul>\n<li>Build and maintain strong working relationships across the organization, from team members who deliver services day to day to senior managers shaping broader CX Services priorities.</li>\n</ul>\n<ul>\n<li>Partner with peers across the CX Services team to create consistent service experiences and ensure offerings are sequenced effectively across the customer lifecycle.</li>\n</ul>\n<ul>\n<li>Create and maintain field enablement materials such as playbooks, talk tracks, objection handling guides, and training resources that help teams deliver services at scale and improve readiness, consistency, and time to delivery.</li>\n</ul>\n<p><strong>What you’ll bring</strong></p>\n<ul>\n<li>Significant experience in professional services, customer success, solutions architecture, or product management within a SaaS environment.</li>\n</ul>\n<ul>\n<li>Strong foundation in DevOps, application development, software development lifecycle, or security concepts, with the ability to apply that knowledge when designing credible services for a technical product space.</li>\n</ul>\n<ul>\n<li>Familiarity with AI and machine learning workflows, large language model capabilities, and agent-based systems, especially in the context of enterprise adoption and change management.</li>\n</ul>\n<ul>\n<li>A clearly AI-forward approach to work, with practical experience using AI tools to improve speed, quality, synthesis, or prioritization in your day-to-day responsibilities.</li>\n</ul>\n<ul>\n<li>Strong communication and stakeholder management skills, with the ability to work effectively across a remote, asynchronous organization and adapt your message for different audiences.</li>\n</ul>\n<ul>\n<li>Strong writing skills, including the ability to create clear requirements, concise summaries, and field-ready materials with minimal revision.</li>\n</ul>\n<p><strong>About the team</strong></p>\n<p>The CX Services team is part of CX Engineering at GitLab. We design, enable, and improve the service offerings that help customers achieve business outcomes across GitLab&#39;s modernization journeys, including AI, Security, and DevOps.</p>\n<p>Our focus is on building the structures that let customer-facing teams deliver consistent, scalable services.</p>\n<p>You&#39;ll work with a team that links strategy to execution by turning customer needs, field insight, and product direction into practical services and internal capabilities.</p>\n<p>We partner closely with organizations across Professional Services, Customer Success, Education Services, and CX Engineering Platform, helping create a more consistent customer experience across the lifecycle.</p>\n<p>We&#39;re a good team for someone who enjoys solving problems that require both systems thinking and cross-functional work, especially in a company that values transparency, iteration, and asynchronous work.</p>\n<p>Our work is cross-functional, outcome-oriented, and closely tied to how we help customers adopt the platform more effectively at scale.</p>\n<p>How GitLab Supports Full-Time Employees</p>\n<ul>\n<li>Benefits to support your health, finances, and well-being</li>\n</ul>\n<ul>\n<li>Flexible Paid Time Off</li>\n</ul>\n<ul>\n<li>Team Member Resource Groups</li>\n</ul>\n<ul>\n<li>Equity Compensation &amp; Employee Stock Purchase Plan</li>\n</ul>\n<ul>\n<li>Growth and Development Fund</li>\n</ul>\n<ul>\n<li>Parental leave</li>\n</ul>\n<ul>\n<li>Home office support</li>\n</ul>\n<p>Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement.</p>\n<p>Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification.</p>\n<p>If you&#39;re excited about this role, please apply and allow our recruiters to assess your application.</p>\n<p>Country Hiring Guidelines: GitLab hires new team members in countries around the world.</p>\n<p>All of our roles are remote, however some roles may carry specific location-based eligibility requirements.</p>\n<p>Our Talent Acquisition team can help answer any questions about location after starting the recruiting process.</p>\n<p>Privacy Policy: Please review our Recruitment Privacy Policy.</p>\n<p>Your privacy is important to us.</p>\n<p>GitLab is proud to be an equal opportunity workplace and is an affirmative action employer.</p>\n<p>GitLab’s policies and practices relating to recruitment, employment, and termination are designed to ensure equal employment opportunities without discrimination or harassment based on race, color, religion, sex, national origin, age, disability, veteran status, marital status, sexual orientation, gender identity, or any other protected characteristic as established by law.</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_d67cb8b7-43f","directApply":true,"hiringOrganization":{"@type":"Organization","name":"GitLab","sameAs":"https://about.gitlab.com/","logo":"https://logos.yubhub.co/about.gitlab.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/gitlab/jobs/8481256002","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Professional services","Customer success","Solutions architecture","Product management","DevOps","Application development","Software development lifecycle","Security concepts","AI","Machine learning","Large language model capabilities","Agent-based systems"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:50:03.857Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Professional services, Customer success, Solutions architecture, Product management, DevOps, Application development, Software development lifecycle, Security concepts, AI, Machine learning, Large language model capabilities, Agent-based systems"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6d742066-b4f"},"title":"Anthropic Fellows Program — AI Safety","description":"<p>The Anthropic Fellows Program is a 4-month full-time research opportunity designed to foster AI research and engineering talent. As a fellow, you will work on an empirical project aligned with our research priorities, with the goal of producing a public output. You will have direct mentorship from Anthropic researchers, access to a shared workspace, and connection to the broader AI safety and security research community. The expected base stipend for this role is $3,850 USD per week, with an expectation of 40 hours per week for 4 months.</p>\n<p>The program is open to individuals with a strong technical background in computer science, mathematics, or physics, and who are motivated by making sure AI is safe and beneficial for society as a whole. You will be part of a diverse team of researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p>\n<p>As a fellow, you will have the opportunity to work on projects in select AI safety research areas, such as scalable oversight, adversarial robustness and AI control, model organisms, model internals/mechanistic interpretability, and AI welfare. You will also have access to our Alignment Science and Frontier Red Team blogs, which feature past projects and research directions.</p>\n<p>To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program. 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As a Staff Engineer, you will be responsible for leading the technical vision for ML-powered messaging features, architecting and delivering intelligent capabilities end-to-end, and partnering deeply with ML and product teams.</p>\n<p>The Difference You Will Make:</p>\n<p>As a Staff Engineer on the team, you will define and drive the technical strategy for integrating ML capabilities into Airbnb&#39;s messaging products, including smart replies, message classification, content moderation, translation, and conversational assistance. You will also own the full lifecycle of ML-powered features: from prototyping and experimentation through launch, monitoring, and iteration.</p>\n<p>A Typical Day:</p>\n<ul>\n<li>Design, build, and operate the systems that serve ML models within the messaging stack, with a focus on latency, reliability, and scalability</li>\n<li>Write and review technical designs that solve large, open-ended problems at the intersection of ML and product engineering without clearly-known solutions</li>\n<li>Partner with ML, data science, and product teams to identify high-value opportunities, establish evaluation criteria, and close the gap between offline model performance and production impact</li>\n<li>Collaborate with other engineers and cross-functional partners across Messaging, Trust &amp; Safety, Localization, and Platform organizations to align on long-term technical solutions</li>\n<li>Mentor, guide, advocate, and support the career growth of individual contributors</li>\n<li>Establish engineering standards for ML integration across the messaging surface, including feature flagging, A/B testing, observability, and graceful degradation</li>\n</ul>\n<p>Your Expertise:</p>\n<ul>\n<li>9+ years of relevant engineering hands-on work experience</li>\n<li>Bachelors, Masters, or PhD in CS or related field</li>\n<li>Demonstrated experience building and shipping ML-powered product features in production environments, including model serving, feature pipelines, online/offline evaluation, and monitoring</li>\n<li>Exceptional architecture abilities and experience with architectural patterns of large, high-scale applications</li>\n<li>Familiarity with NLP/NLU techniques and large language models, particularly as applied to messaging, conversational AI, or content understanding</li>\n<li>Shipped several large-scale projects with multiple dependencies across teams, specifically at the intersection of ML infrastructure and product engineering</li>\n<li>Technical leadership and strong communication skills with the ability to translate between ML research, product goals, and engineering execution</li>\n<li>Experience operating distributed, real-time systems at scale with high reliability requirements</li>\n<li>Experience with real-time messaging systems or event-driven architectures</li>\n<li>Familiarity with ML infrastructure at scale (e.g., feature stores, model registries, online inference platforms)</li>\n<li>Prior work on trust &amp; safety, content moderation, or internationalization in a messaging context</li>\n<li>Experience with LLM-based product features, including prompt engineering, retrieval-augmented generation, or fine-tuning</li>\n</ul>\n<p>How We&#39;ll Take Care of You:</p>\n<p>Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.</p>\n<p>Pay Range: $204,000-$255,000 USD</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_e3b1c38b-ef1","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Airbnb","sameAs":"https://www.airbnb.com/","logo":"https://logos.yubhub.co/airbnb.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/airbnb/jobs/7655958","x-work-arrangement":"remote","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$204,000-$255,000 USD","x-skills-required":["ML-powered product features","model serving","feature pipelines","online/offline evaluation","monitoring","architectural patterns","NLP/NLU techniques","large language models","messaging","conversational AI","content understanding","distributed, real-time systems","real-time messaging systems","event-driven architectures","ML infrastructure","feature stores","model registries","online inference platforms","trust & safety","content moderation","internationalization","LLM-based product features","prompt engineering","retrieval-augmented generation","fine-tuning"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:49:16.839Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - USA"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"ML-powered product features, model serving, feature pipelines, online/offline evaluation, monitoring, architectural patterns, NLP/NLU techniques, large language models, messaging, conversational AI, content understanding, distributed, real-time systems, real-time messaging systems, event-driven architectures, ML infrastructure, feature stores, model registries, online inference platforms, trust & safety, content moderation, internationalization, LLM-based product features, prompt engineering, retrieval-augmented generation, fine-tuning","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":204000,"maxValue":255000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_70a8d742-39f"},"title":"Staff Model UX Designer, Personalization, GeminiApp","description":"<p><strong>Snapshot</strong></p>\n<p>We&#39;re hiring a Staff Model UX Designer to play a critical role in our Personalization initiatives. 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As a Senior Product Manager, you will play a central role in shaping our brand-new product area, defining how AI agents are authenticated, authorized, and governed. 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You&#39;ll develop novel architectures and training methodologies for RLHF, research new approaches to LLM-based evaluation and grading (including rubric-based methods), and investigate techniques to identify and mitigate reward hacking.</p>\n<p>You&#39;ll collaborate closely with teams across Anthropic, including Finetuning, Alignment Science, and our broader research organization, to ensure your work translates into concrete improvements in both model capabilities and safety.</p>\n<p>We&#39;re looking for someone who can drive ambitious research agendas while also shipping practical improvements to production systems. You&#39;ll have the opportunity to work on some of the most important open problems in AI alignment, with access to frontier models and significant computational resources.</p>\n<p>Your work will directly advance the science of how we train AI systems to be both highly capable and safe.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Lead research on novel reward model architectures and training approaches for RLHF</li>\n</ul>\n<ul>\n<li>Develop and evaluate LLM-based grading and evaluation methods, including rubric-driven approaches that improve consistency and interpretability</li>\n</ul>\n<ul>\n<li>Research techniques to detect, characterize, and mitigate reward hacking and specification gaming</li>\n</ul>\n<ul>\n<li>Design experiments to understand reward model generalization, robustness, and failure modes</li>\n</ul>\n<ul>\n<li>Collaborate with the Finetuning team to translate research insights into improvements for production training pipelines</li>\n</ul>\n<ul>\n<li>Contribute to research publications, blog posts, and internal documentation</li>\n</ul>\n<ul>\n<li>Mentor other researchers and help build institutional knowledge around reward modeling</li>\n</ul>\n<p>You may be a good fit if you:</p>\n<ul>\n<li>Have a track record of research contributions in reward modeling, RLHF, or closely related areas of machine learning</li>\n</ul>\n<ul>\n<li>Have experience training and evaluating reward models for large language models</li>\n</ul>\n<ul>\n<li>Are comfortable designing and running large-scale experiments with significant computational resources</li>\n</ul>\n<ul>\n<li>Can work effectively across research and engineering, iterating quickly while maintaining scientific rigor</li>\n</ul>\n<ul>\n<li>Enjoy collaborative research and can communicate complex ideas clearly to diverse audiences</li>\n</ul>\n<ul>\n<li>Care deeply about building AI systems that are both highly capable and safe</li>\n</ul>\n<p>Strong candidates may also:</p>\n<ul>\n<li>Have published research on reward modeling, preference learning, or RLHF</li>\n</ul>\n<ul>\n<li>Have experience with LLM-as-judge approaches, including calibration and reliability challenges</li>\n</ul>\n<ul>\n<li>Have worked on reward hacking, specification gaming, or related robustness problems</li>\n</ul>\n<ul>\n<li>Have experience with constitutional AI, debate, or other scalable oversight approaches</li>\n</ul>\n<ul>\n<li>Have contributed to production ML systems at scale</li>\n</ul>\n<ul>\n<li>Have familiarity with interpretability techniques as applied to understanding reward model behavior</li>\n</ul>\n<p>The annual compensation range for this role is $350,000-$500,000 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</ul>\n<ul>\n<li>Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience</li>\n</ul>\n<ul>\n<li>Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position</li>\n</ul>\n<p>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.</p>\n<p>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.</p>\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. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.</p>\n<p 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_8549c317-12f","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5024835008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$350,000-$500,000 USD","x-skills-required":["reward modeling","RLHF","large language models","novel architectures","training methodologies","evaluation and grading","rubric-based methods","reward hacking","specification gaming","generalization","robustness","failure modes","computational resources","scientific rigor","communication skills","interpretability techniques"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:47:13.514Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote-Friendly (Travel Required) | San Francisco, CA"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"reward modeling, RLHF, large language models, novel architectures, training methodologies, evaluation and grading, rubric-based methods, reward hacking, specification gaming, generalization, robustness, failure modes, computational resources, scientific rigor, communication skills, interpretability techniques","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":350000,"maxValue":500000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2075095a-d93"},"title":"Senior Software Engineer, BizTech(AI Products)","description":"<p><strong>Job Title</strong></p>\n<p>Senior Software Engineer, AI Products (India)</p>\n<p><strong>Company Overview</strong></p>\n<p>Airbnb is a global online marketplace for booking accommodations, with over 5 million hosts and 2 billion guest arrivals.</p>\n<p><strong>The Community You Will Join</strong></p>\n<p>The Airfam Products team exists to make every Airbnb employee more productive through a unified digital headquarters experience. As part of a 13-person cross-functional team of engineers, designers, researchers, and product managers, you&#39;ll work on platforms that serve Airbnb&#39;s entire global workforce. Our portfolio includes One Airbnb (the company&#39;s internal cultural hub with enterprise search, people profiles, and AI-powered chat), OneChat (Airbnb&#39;s enterprise AI assistant enabling secure LLM interactions), and a suite of tools that power how employees discover information, connect with colleagues, and get work done. 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You&#39;ll collaborate with teammates across global time zones, with primary alignment to Pacific Time for key meetings.</p>\n<p><strong>Our Commitment to Inclusion &amp; Belonging</strong></p>\n<p>Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.</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_2075095a-d93","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Airbnb","sameAs":"https://www.airbnb.com/","logo":"https://logos.yubhub.co/airbnb.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/airbnb/jobs/7730723","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["software engineering","production AI/ML systems","Large Language Models (LLMs)","backend technologies (TypeScript, Go, or Java)","API design (REST, GraphQL)","cloud infrastructure (AWS, GCP, or Azure)"],"x-skills-preferred":["master's or PhD in Computer Science, Machine Learning, or related field","experience building AI agents and multi-agent systems","experience building integrations using MCP","experience with containerization and orchestration (Docker, Kubernetes)","background in building enterprise-grade internal tools and developer productivity platforms","experience with frontend technologies (React, Next.js) for full-stack AI product development"],"datePosted":"2026-04-18T15:46:37.928Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bangalore, India"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"software engineering, production AI/ML systems, Large Language Models (LLMs), backend technologies (TypeScript, Go, or Java), API design (REST, GraphQL), cloud infrastructure (AWS, GCP, or Azure), master's or PhD in Computer Science, Machine Learning, or related field, experience building AI agents and multi-agent systems, experience building integrations using MCP, experience with containerization and orchestration (Docker, Kubernetes), background in building enterprise-grade internal tools and developer productivity platforms, experience with frontend technologies (React, Next.js) for full-stack AI product development"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_26b9d76f-c85"},"title":"Research Engineer, Universes","description":"<p>We&#39;re looking for Research Engineers to help us build the next generation of training environments for capable and safe agentic AI.</p>\n<p>This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to research direction. 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You will make fundamental contributions to the development of the Anthropic Economic Index, establishing new methodologies to measure the usage, diffusion, and impact of AI throughout the economy using privacy-preserving tools and novel data sources. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigour will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions.</p>\n<p>Our team combines rigorous empirical methods with novel measurement approaches. We&#39;re building first-of-its-kind datasets tracking AI&#39;s impact on labor markets, productivity, and economic transformation. 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They will have a strong track record of empirical research, particularly studies combining novel data sources and economic theory or those implementing frontier methods in causal inference and machine learning.</p>\n<p>Some examples of our recent work include:</p>\n<ul>\n<li>Anthropic Economic Index Report: Economic Primitives</li>\n<li>Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption</li>\n<li>Estimating AI productivity gains from Claude conversations</li>\n<li>The Anthropic Economic Index</li>\n</ul>\n<p>For this role, we&#39;re looking for candidates who can combine rigorous economic analysis with novel measurement approaches to understand AI&#39;s transformative effects on the economy.</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_9327ea90-f95","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5018472008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$300,000-$405,000 USD","x-skills-required":["PhD in Economics","Strong track record of empirical research","Experience with novel data sources and economic theory","Frontier methods in causal inference and machine learning","Python, R, SQL, or similar tools for large-scale data analysis"],"x-skills-preferred":["Labor market analysis and occupational change","Task-based approaches to technological transformation","Large-scale data analysis and econometric methods","Large language models for social science research","Policy-relevant economic research"],"datePosted":"2026-04-18T15:45:19.919Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"PhD in Economics, Strong track record of empirical research, Experience with novel data sources and economic theory, Frontier methods in causal inference and machine learning, Python, R, SQL, or similar tools for large-scale data analysis, Labor market analysis and occupational change, Task-based approaches to technological transformation, Large-scale data analysis and econometric methods, Large language models for social science research, Policy-relevant economic research","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":300000,"maxValue":405000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_eda84ece-394"},"title":"Security Engineer, Detection & Response","description":"<p>At Anthropic, we are pioneering new frontiers in AI that have the potential to greatly benefit society. 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You will lead cybersecurity Incident Response efforts covering diverse domains from external attacks to insider threats involving all layers of Anthropic&#39;s technology stack.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Developing and deploying novel tooling that may leverage Large Language Models to enhance detection, investigation, and response capabilities</li>\n<li>Creating and optimizing detections, playbooks, and workflows to quickly identify and respond to potential incidents</li>\n<li>Reviewing Incident Response metrics and procedures and driving continuous improvement</li>\n<li>Working cross-functionally with other security and engineering teams</li>\n</ul>\n<p>Note: This position will require participation in an on-call rotation.</p>\n<p>To be successful in this role, you will need:</p>\n<ul>\n<li>3+ years of software engineering experience, with security experience a plus</li>\n<li>5+ years of detection engineering, incident response, or threat hunting experience</li>\n<li>A solid understanding of cloud environments and operations</li>\n<li>Experience working with engineering teams in a SaaS environment</li>\n<li>Exceptional communication and collaboration skills</li>\n<li>An ability to lead projects with little guidance</li>\n<li>The ability to pick up new languages and technologies quickly</li>\n<li>Experience handling security incidents and investigating anomalies as part of a team</li>\n<li>Knowledge of EDR, SIEM, SOAR, or related security tools</li>\n</ul>\n<p>Strong candidates may also have experience with:</p>\n<ul>\n<li>Performing security operations or investigations involving large-scale Kubernetes environments</li>\n<li>A high level of proficiency in Python and query languages such as SQL</li>\n<li>Analyzing attack behavior and prototyping high-quality detections</li>\n<li>Threat intelligence, malware analysis, infrastructure as code, detection engineering, or forensics</li>\n<li>Contributing to a high-growth startup environment</li>\n</ul>\n<p>If you&#39;re interested in this role, please submit an application, even if you don&#39;t believe you meet every single qualification. 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Build multi-agent frameworks and secure gateways while integrating real-time security gates and identity standards. By mentoring Security and R&amp;D to define the MLSecOps roadmap, you&#39;ll ensure a &#39;secure-by-default&#39; future for agentic workflows and resilient AI innovation.</p>\n<p>Responsibilities:</p>\n<p>Serve as the primary subject matter expert for all AI and machine learning security initiatives across security and R&amp;D.</p>\n<p>Design and manage AI gateways to provide a centralized control plane for authentication and authorization and rate limiting across all model and tool interactions.</p>\n<p>Build and maintain an autonomous security agentic framework that utilizes multi agent orchestration for end to end investigation and alert triage and remediation.</p>\n<p>Develop agentic identity models using OAuth 2.1 to propagate identity across trust boundaries and prevent the confused deputy problem.</p>\n<p>Help govern the AI augmented software development lifecycle by integrating real time security gates into the developer environment and CI/CD pipeline.</p>\n<p>Manage Agentic Security Solutions that secure AI lifecycle and manage AI workloads at runtime.</p>\n<p>Author company wide AI security standards and implement these security checks across Twilio&#39;s stack.</p>\n<p>Implement human in the loop checkpoints and transactional safety protocols for high impact or destructive agentic actions.</p>\n<p>Partner with engineering leadership to set the long term roadmap for identity centric security and automated posture management.</p>\n<p>Act as a knowledge multiplier by mentoring security engineers and developing secure by default paved road templates for R&amp;D teams</p>\n<p>Qualifications:</p>\n<p>8+ years of experience in security engineering with at least 3 years focused on AI or machine learning security operations (MLSecOps).</p>\n<p>Expertise in orchestrating multi-agent systems with AWS Strands, LangGraph, and CrewAI, specializing in runtime isolation, PII redaction, and defending against indirect prompt injection in agentic environments.</p>\n<p>Hands-on experience with AI-specific frameworks (e.g., MITRE ATLAS, MAESTRO, OWASP Top 10 for LLMs/Agents/MCP) to threat model and defend against a wide spectrum of risks, including direct/indirect prompt injection, training data poisoning, tool poisoning, and data exfiltration within agentic workflows.</p>\n<p>Proficiency in securing end-to-end AI pipelines, from data ingestion and training to model deployment and monitoring.</p>\n<p>Strong communication skills to translate complex AI risks into actionable business logic for stakeholders.</p>\n<p>Desired:</p>\n<p>Hands-on experience in modern application security tooling including SAST and SCA and DAST with experience adapting these tools to catch AI specific vulnerabilities like indirect prompt injection.</p>\n<p>Expertise in identity standards including OAuth 2.1 and PKCE.</p>\n<p>Experience with AI Red Teaming and conducting adversarial simulations against Large Language Models (LLMs) and agentic systems.</p>\n<p>Proficiency in at least one general programming language (Python, Go, etc) with experience in container security and workload isolation.</p>\n<p>Proven ability to operate with autonomy and drive high impact outcomes in ambiguous environments by identifying and executing on critical projects without predefined roadmaps or direct supervision.</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_0ae6f8dc-4fd","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Twilio","sameAs":"https://www.twilio.com/","logo":"https://logos.yubhub.co/twilio.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/twilio/jobs/7821462","x-work-arrangement":"remote","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["security engineering","AI and machine learning security","multi-agent systems","AWS Strands","LangGraph","CrewAI","runtime isolation","PII redaction","indirect prompt injection","AI-specific frameworks","MITRE ATLAS","MAESTRO","OWASP Top 10 for LLMs/Agents/MCP","end-to-end AI pipelines","data ingestion","training","model deployment","monitoring","strong communication skills"],"x-skills-preferred":["modern application security tooling","SAST and SCA and DAST","identity standards","OAuth 2.1","PKCE","AI Red Teaming","adversarial simulations","Large Language Models","container security","workload isolation"],"datePosted":"2026-04-18T15:44:10.579Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - 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Not all strong candidates will meet every single qualification as listed.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_bd9625d9-99b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4778843008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$320,000-$405,000 USD","x-skills-required":["Python","PyTorch","TensorFlow","JAX","Cloud platforms (AWS, GCP)","Container orchestration (Kubernetes)","Distributed systems principles","Data engineering tools (Spark, Airflow, streaming systems)"],"x-skills-preferred":["Large language models and modern transformer architectures","A/B testing frameworks and experimentation infrastructure 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candidates at various experience levels, with a preference for senior engineers who have hands-on experience with frontier AI systems.</p>\n<p>However, proficiency in Python, deep learning frameworks, and distributed computing is required for this role.</p>\n<p>The annual compensation range for this role is $350,000-$500,000 USD.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_e850d882-42f","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4613592008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$350,000-$500,000 USD","x-skills-required":["Python","Deep learning frameworks","Distributed computing","ML systems","Large-scale 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Engineer, Production Model Post-Training","description":"<p>About Anthropic</p>\n<p>Anthropic&#39;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole.</p>\n<p>About the role</p>\n<p>Anthropic&#39;s production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you&#39;ll train our base models through the complete post-training stack to deliver the production Claude models that users interact with.</p>\n<p>You&#39;ll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models.</p>\n<p>Responsibilities</p>\n<ul>\n<li>Implement and optimize post-training techniques at scale on frontier models</li>\n<li>Conduct research to develop and optimize post-training recipes that directly improve production model quality</li>\n<li>Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation</li>\n<li>Develop tools to measure and improve model performance across various dimensions</li>\n<li>Collaborate with research teams to translate emerging techniques into production-ready implementations</li>\n<li>Debug complex issues in training pipelines and model behavior</li>\n<li>Help establish best practices for reliable, reproducible model post-training</li>\n</ul>\n<p>You may be a good fit if you:</p>\n<ul>\n<li>Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities</li>\n<li>Adapt quickly to changing priorities</li>\n<li>Maintain clarity when debugging complex, time-sensitive issues</li>\n<li>Have strong software engineering skills with experience building complex ML systems</li>\n<li>Are comfortable working with large-scale distributed systems and high-performance computing</li>\n<li>Have experience with training, fine-tuning, or evaluating large language models</li>\n<li>Can balance research exploration with engineering rigor and operational reliability</li>\n<li>Are adept at analyzing and debugging model training processes</li>\n<li>Enjoy collaborating across research and engineering disciplines</li>\n<li>Can navigate ambiguity and make progress in fast-moving research environments</li>\n</ul>\n<p>Strong candidates may also:</p>\n<ul>\n<li>Have experience with LLMs</li>\n<li>Have a keen interest in AI safety and responsible deployment</li>\n</ul>\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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You will play a crucial role in shaping how Small Businesses communicate, operate, and scale using generative AI.\\n\\nKey Responsibilities:\\n\\n<em> Drive big product vision &amp; build from the ground up: Lead the technical and design vision for Gemini’s Small Business experiences, designing and building foundational, 0-to-1 features and capabilities entirely from scratch.\\n\\n</em> Define business &amp; response strategy: Develop business strategies, communication frameworks, system instructions, and rubrics specifically designed to improve model response quality and relevance for use cases.\\n\\n<em> Architect intuitive AI experiences: Lead the design of user interfaces and consumer experiences for Gemini across diverse platforms, ensuring natural, efficient, and deeply helpful multimodal interactions.\\n\\n</em> Shape LLM behavior: Partner closely with Product, Engineering, and other teams to define user-centered quality standards, establish evaluation methods, and directly shape the behavior and responses of underlying LLM models.\\n\\n<em> Design with a systems-thinking approach: Apply a macro-level systems-thinking approach to design, understanding the impact of individual components on the overall AI-powered experience, optimized for AI&#39;s probabilistic nature.\\n\\n</em> Craft visually compelling &amp; 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One of these risks is the potential for LLMs to enable adversaries to cause harm by automating the attacks that today are carried out by human cybercrime groups, but in the future may be easily carried out by humans misusing LLMs.</p>\n<p>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>We are hiring security specialists who are experienced at exploitation and remediation, and are interested in understanding how LLMs could cause harm in the future, so that we can better prepare for this future and mitigate these risks before they arise.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Triage any vulnerabilities discovered, coordinate and assist the external and open-source community in remediation</li>\n<li>Write scaffolds designed to automate typical traditional attack techniques to help clarify our defensive problem selection</li>\n<li>Research how adversaries might misuse LLMs to identify and exploit vulnerabilities at scale in the future</li>\n<li>Develop promising defensive strategies that could mitigate the ability of adversaries to misuse models in harmful ways</li>\n<li>Work with a small, senior team of engineers and researchers to enact a forward-looking security plan</li>\n</ul>\n<p>You may be a good fit if you have:</p>\n<ul>\n<li>3+ years experience with pentesting, vulnerability research, or other offensive security experience</li>\n<li>Senior-level knowledge in at least one related topic area (reverse engineering, network security, exploitation, physical security)</li>\n<li>A history demonstrating desire to do the &#39;dirty work&#39; that results in high-quality outputs</li>\n<li>Software engineering experience</li>\n<li>Demonstrated success in bringing clarity and ownership to ambiguous technical problems</li>\n<li>Proven ability to lead cross-functional security initiatives and navigate complex organisational dynamics</li>\n</ul>\n<p>Strong candidates may also have:</p>\n<ul>\n<li>Published research papers on computer security, language modeling, or related topics; or given talks at Defcon, Blackhat, CCC, or related venues</li>\n<li>Familiarity with large language models and how they work; for example, you may have written agent scaffolds</li>\n<li>Reported CVEs, or been awarded for bug bounty vulnerabilities</li>\n<li>Contributed to open-source projects in LLM- or security-adjacent repositories</li>\n</ul>\n<p>The annual compensation range for this role is $320,000-$405,000 USD.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_28f97bd7-3d7","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5123011008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$320,000-$405,000 USD","x-skills-required":["pentesting","vulnerability research","offensive security","reverse engineering","network security","exploitation","physical security","software engineering"],"x-skills-preferred":["large language models","agent scaffolds","CVEs","bug bounty vulnerabilities","open-source projects"],"datePosted":"2026-04-18T15:41:01.125Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"pentesting, vulnerability research, offensive security, reverse engineering, network security, exploitation, physical security, software engineering, large language models, agent scaffolds, CVEs, bug bounty vulnerabilities, open-source projects","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":320000,"maxValue":405000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c0df6b64-aad"},"title":"Head of Solutions Architects, Applied AI (Korea)","description":"<p><strong>Job Title</strong></p>\n<p>Head of Solutions Architects, Applied AI (Korea)</p>\n<p><strong>About Anthropic</strong></p>\n<p>Anthropic&#39;s mission is to create reliable, interpretable, and steerable AI systems. The company 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>As the founding leader of Applied AI Solutions Architecture in Korea, you will drive the adoption of frontier AI by enabling the deployment of Anthropic&#39;s products (Claude for Enterprise, Claude Code, and API) across Korean enterprises and digital-first organisations. You&#39;ll leverage your technical skills and consultative sales experience to drive positive AI transformation that addresses our customers&#39; business needs, meets their technical requirements, and provides a high degree of reliability and safety.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Build and manage the foundational team of Applied AI professionals in Seoul (Solutions Architects and Product Engineers) providing both technical guidance and career development</li>\n<li>Set goals and reviews for your team, promoting growth and output</li>\n<li>Work with a handful of highest-value enterprise customers on their overall AI adoption strategies, focusing on pre-sales technical excellence including use case scoping, technical champion building, and POC execution</li>\n<li>Partner closely with your aligned GTM leadership to understand customer requirements &amp; co-build GTM strategies to drive adoption for Korean enterprise customers</li>\n<li>Contribute to thought leadership through conference presentations, webinars, and technical content creation</li>\n<li>Own the technical portions of pre-sales engagements, ensuring your team provides compelling demos and validates enterprise customer ROI from Anthropic products</li>\n<li>Drive collaboration from cross-functional teams to influence and unify stakeholders at all levels of the organisation to drive business outcomes</li>\n<li>Travel regularly to customer sites for executive-level sessions, technical workshops, and building relationships</li>\n<li>Establish a shared vision for creating solutions that enable beneficial and safe AI in technology products</li>\n<li>Lead the vision, strategy, and execution of innovative solutions that leverage our latest models&#39; capabilities</li>\n<li>Stay current with emerging AI/ML trends and competitive landscape in the Korean enterprise tech sector</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>7+ years of experience as a Solutions Architect, Sales Engineer, or similar pre-sales technical role</li>\n<li>3+ years of technical go-to-market management experience, specifically managing pre-sales teams</li>\n<li>Native or business-level fluency in Korean and professional proficiency in English</li>\n<li>Experience working with Korean enterprise customers and understanding local business culture and decision-making processes</li>\n<li>Experience with the unique technical requirements and technical procurement process of enterprise tech companies</li>\n<li>Deep technical proficiency with enterprise AI deployments, API integrations, and production LLM use cases</li>\n<li>Have an organisational mindset and enjoy building foundational teams in a relatively unstructured environment</li>\n<li>Have excellent communication, collaboration, and coaching abilities</li>\n<li>Are comfortable dealing with highly uncertain, ambiguous, and fast-moving environments typical of the tech industry</li>\n<li>Strong executive presence and ability to foster deep relationships with technical leaders and engineering teams</li>\n<li>Have at least a high level familiarity with the architecture and operation of large language models and/or ML in general</li>\n<li>Experience with prompt engineering, LLM evaluation, and architecting AI-powered systems</li>\n<li>Make ambiguous problems clear and identify core principles that can translate across scenarios</li>\n<li>Have a passion for making powerful technology safe and societally beneficial</li>\n<li>Think creatively about the risks and benefits of new technologies, and think beyond past checklists and playbooks</li>\n<li>Stay up-to-date and informed by taking an active interest in emerging research and industry trends</li>\n<li>Understanding of developer tooling, SDKs, and technical integration patterns common in enterprise tech companies</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary and benefits package</li>\n<li>Opportunity to work with a talented and diverse team</li>\n<li>Professional development and growth opportunities</li>\n<li>Flexible work arrangements</li>\n</ul>\n<p><strong>How to Apply</strong></p>\n<p>If you&#39;re interested in this opportunity, please submit your resume and a cover letter explaining why you&#39;re a great fit for this role. We can&#39;t wait to hear from you!</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_c0df6b64-aad","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5064817008","x-work-arrangement":"hybrid","x-experience-level":"executive","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Solutions Architect","Sales Engineer","Pre-sales Technical Role","Technical Go-to-Market Management","Enterprise AI Deployments","API Integrations","Production LLM Use Cases","Large Language Models","Machine Learning","Prompt Engineering","LLM Evaluation","AI-Powered Systems"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:40:39.535Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Seoul, South Korea"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Solutions Architect, Sales Engineer, Pre-sales Technical Role, Technical Go-to-Market Management, Enterprise AI Deployments, API Integrations, Production LLM Use Cases, Large Language Models, Machine Learning, Prompt Engineering, LLM Evaluation, AI-Powered Systems"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_516a85f4-c5e"},"title":"Industry Principal, Insurance","description":"<p>As the Industry Principal, Insurance at Anthropic, you will serve as the technical and strategic face of Claude to the world&#39;s leading insurance carriers, brokers, reinsurers, and insurtech companies. You&#39;ll combine deep insurance domain expertise with technical credibility to help customers envision, architect, and realise transformational AI solutions,while building Anthropic&#39;s reputation as the trusted AI platform for one of the most complex and regulated industries in the world.</p>\n<p>This role sits at the intersection of technical leadership, customer engagement, product strategy, and internal enablement. You&#39;ll work directly with CIOs, CTOs, Chief Underwriting Officers, Chief Claims Officers, and technology leaders at major insurers and brokers to design solutions that address their most critical challenges,from underwriting automation and claims processing to fraud detection and customer experience. Your insights will flow directly to Product and Research, shaping Claude&#39;s roadmap for insurance. Equally important, you&#39;ll enable Anthropic&#39;s GTM teams with deep domain expertise, thought leadership content, and strategic guidance.</p>\n<p>With AI poised to transform insurance operations and the industry seeking partners who understand their unique challenges, you&#39;ll play a pivotal role in establishing Anthropic as the AI platform of choice for insurers worldwide.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Technical Evangelism &amp; Thought Leadership: Represent Anthropic&#39;s technical vision to the insurance industry through conference keynotes, executive briefings, whitepapers, and industry advisory boards. Establish Claude as the leading AI platform for P&amp;C, Life, and Reinsurance markets.</li>\n</ul>\n<ul>\n<li>Strategic Customer Engagement: Serve as executive technical sponsor for strategic insurance accounts, engaging CIOs, CTOs, Chief Underwriting Officers, Chief Claims Officers, and Heads of AI/ML on enterprise AI strategy. Build peer-to-peer relationships that position Anthropic as a strategic transformation partner.</li>\n</ul>\n<ul>\n<li>Product Partnership &amp; Roadmap Influence: Translate customer requirements and competitive dynamics into product priorities. Partner closely with Product and Research to develop insurance-specific capabilities including model governance, explainability, audit logging, and regulatory compliance features.</li>\n</ul>\n<ul>\n<li>Pricing &amp; Commercial Strategy: Contribute to pricing and packaging decisions with insurance market insight. Understand value drivers for different insurance segments, competitive positioning, and deal structuring that aligns with how insurers buy technology.</li>\n</ul>\n<ul>\n<li>Internal Enablement &amp; Advocacy: Train and uplift Anthropic&#39;s GTM teams on insurance domain expertise, use cases, and buyer personas. Create enablement content, conduct training sessions, and serve as the internal authority on all things insurance. Influence without authority across the organisation.</li>\n</ul>\n<ul>\n<li>Regulatory &amp; Compliance Navigation: Partner internally and externally to develop thought leadership regarding AI governance frameworks aligned with state insurance regulations, NAIC guidelines, and international requirements. Help customers understand model risk management, explainability requirements, and responsible AI practices for insurance.</li>\n</ul>\n<ul>\n<li>Ecosystem Partnership: Build technical relationships with GSIs (Deloitte, Accenture, McKinsey), cloud providers (AWS, Azure, GCP), and insurance technology vendors (Guidewire, Duck Creek, Majesco).</li>\n</ul>\n<p><strong>Requirements:</strong></p>\n<ul>\n<li>Have 20+ years of experience in technology and/or business roles with at least 8 years in senior leadership positions (CTO, VP Engineering, Chief Architect, Chief Underwriting Officer, Head of Claims Technology, Distinguished Engineer) in insurance</li>\n</ul>\n<ul>\n<li>Have deep domain expertise across multiple insurance segments,P&amp;C (personal and commercial lines), Life &amp; Annuities, or Reinsurance,with hands-on experience building or operating mission-critical systems</li>\n</ul>\n<ul>\n<li>Have a strong understanding of AI/ML technologies including large language models, with the ability to engage credibly on technical architecture, model behaviour, and system design</li>\n</ul>\n<ul>\n<li>Have established executive networks across insurance technology leadership (CIOs, CTOs, Chief Underwriting Officers) and credibility as a thought leader in the industry</li>\n</ul>\n<ul>\n<li>Have deep knowledge of insurance regulatory requirements (state insurance regulations, NAIC model laws, Solvency II, Lloyd&#39;s requirements) and experience implementing compliant technology solutions</li>\n</ul>\n<ul>\n<li>Are skilled at translating complex technical concepts into business value propositions that resonate with both technical and business stakeholders</li>\n</ul>\n<ul>\n<li>Have experience influencing product roadmaps based on customer feedback and market requirements, working effectively with Product and Engineering teams</li>\n</ul>\n<ul>\n<li>Are passionate about responsible AI development and Anthropic&#39;s mission, with a commitment to helping insurers adopt AI safely and beneficially</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience</li>\n</ul>\n<ul>\n<li>Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience</li>\n</ul>\n<ul>\n<li>Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position</li>\n</ul>\n<ul>\n<li>Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</li>\n</ul>\n<ul>\n<li>Visa sponsorship: We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</li>\n</ul>\n<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_516a85f4-c5e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5133070008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$360,000-$550,000 USD","x-skills-required":["Insurance domain expertise","Technical credibility","Leadership","Customer engagement","Product strategy","Internal enablement","AI/ML technologies","Large language models","Technical architecture","Model behaviour","System design","Insurance regulatory requirements","Compliant technology solutions"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:40:21.565Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Insurance domain expertise, Technical credibility, Leadership, Customer engagement, Product strategy, Internal enablement, AI/ML technologies, Large language models, Technical architecture, Model behaviour, System design, Insurance regulatory requirements, Compliant technology solutions","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":360000,"maxValue":550000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_9974a944-db3"},"title":"Manager, Applied AI (Startups)","description":"<p>As the leader of Applied AI for Startups across EMEA, you will lead Applied AI Architects and Applied AI Engineers to build technical mindshare around Anthropic&#39;s products among early-stage adopters across EMEA.</p>\n<p>You&#39;ll work with the fastest-growing AI-focused startups in the region, driving adoption of frontier AI through bespoke LLM solutions. You&#39;ll build and grow a cross-functional technical team, establish best practices for startup engagements, and represent Anthropic as a technical leader across the region.</p>\n<p>In collaboration with Sales, Product, and Engineering, you&#39;ll help startups incorporate AI into their products and platforms. A core part of this role is building Anthropic&#39;s technical brand across the EMEA startup ecosystem through hands-on engagements, workshops, developer content, and strategic partnerships with accelerators and VCs.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Build, hire, lead, and mentor a team of Applied AI Architects and Applied AI Engineers supporting EMEA Startups</li>\n</ul>\n<ul>\n<li>Partner with EMEA GTM leadership and Sales to build market-specific strategies that drive adoption and technical mindshare among startups</li>\n</ul>\n<ul>\n<li>Engage hands-on with highest-value EMEA startups on advanced LLM integration, deployment, and adoption</li>\n</ul>\n<ul>\n<li>Travel regularly across EMEA for customer workshops, ecosystem events, accelerator demo days, and conferences</li>\n</ul>\n<ul>\n<li>Build technical mindshare among early-adopter startups through developer workshops, technical content, hackathons, and community programmes</li>\n</ul>\n<ul>\n<li>Build relationships with VCs, accelerators, and incubators to position Anthropic as the platform of choice for emerging companies</li>\n</ul>\n<ul>\n<li>Surface product feedback and market intelligence from EMEA startup engagements back to Product and Engineering</li>\n</ul>\n<p>You may be a good fit if you have:</p>\n<ul>\n<li>7+ years of experience as a Forward Deployed Engineer, Customer Engineer, Sales Engineer, Applied AI Architect, or Applied AI Engineer</li>\n</ul>\n<ul>\n<li>Minimum 5+ years of management experience (ideally 7+) leading hands-on, technical, customer-facing teams, with a track record of hiring and scaling teams rapidly</li>\n</ul>\n<ul>\n<li>Experience building AI-native products and working with AI-native startups, ideally across multiple EMEA markets</li>\n</ul>\n<ul>\n<li>Enjoy building distributed teams across geographies in unstructured environments</li>\n</ul>\n<ul>\n<li>Strong executive presence and ability to build deep relationships across diverse cultural contexts</li>\n</ul>\n<ul>\n<li>Familiarity with the architecture and operation of large language models</li>\n</ul>\n<ul>\n<li>Passion for making powerful technology safe and societally beneficial</li>\n</ul>\n<ul>\n<li>Willingness to travel frequently across EMEA (estimated 30–40% travel)</li>\n</ul>\n<p>Nice to have:</p>\n<ul>\n<li>Second-line management experience across different technical functions (e.g., managing both Applied AI Architecture and Engineering leads)</li>\n</ul>\n<ul>\n<li>Founder or early-stage startup/scaleup experience: you understand the pace, constraints, and mindset of the companies you’ll be serving</li>\n</ul>\n<ul>\n<li>Experience operating across multiple EMEA markets with understanding of regional startup ecosystems and go-to-market dynamics</li>\n</ul>\n<ul>\n<li>Proficiency in one or more additional EMEA languages (e.g., French, German, Spanish, Italian, Swedish, Hebrew)</li>\n</ul>\n<p>The annual compensation range for this role is £325,000-£390,000 GBP.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_9974a944-db3","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5142110008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"£325,000-£390,000 GBP","x-skills-required":["Forward Deployed Engineer","Customer Engineer","Sales Engineer","Applied AI Architect","Applied AI Engineer","Large Language Models","AI-Native Products","Startup Ecosystems","Go-To-Market Dynamics"],"x-skills-preferred":["Second-Line Management","Founder or Early-Stage Startup/Scaleup Experience","EMEA Languages"],"datePosted":"2026-04-18T15:40:20.394Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Forward Deployed Engineer, Customer Engineer, Sales Engineer, Applied AI Architect, Applied AI Engineer, Large Language Models, AI-Native Products, Startup Ecosystems, Go-To-Market Dynamics, Second-Line Management, Founder or Early-Stage Startup/Scaleup Experience, EMEA Languages","baseSalary":{"@type":"MonetaryAmount","currency":"GBP","value":{"@type":"QuantitativeValue","minValue":325000,"maxValue":390000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c6c0a57f-a27"},"title":"Research Scientist, Gemini Information Tasks","description":"<p>We are seeking a research scientist to precisely improve Gemini&#39;s information-seeking capabilities. The successful candidate will work on post-training research in Gemini, focusing on quality of information-seeking responses. This role offers an opportunity to explore fundamental issues in modelling and data interventions for information-seeking scenarios, with significant opportunities in shaping Google&#39;s products in this space.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Conduct research on post-training methods for information-seeking scenarios in Gemini, including reinforcement learning and self-supervised training.</li>\n<li>Develop novel evaluation methods for improving model quality, grounding, and factuality.</li>\n<li>Investigate orchestration of tool calls and improved retrieval methods for information-seeking scenarios.</li>\n</ul>\n<p><strong>Requirements:</strong></p>\n<ul>\n<li>PhD in a relevant area, or an equivalent research/publication record.</li>\n<li>Strong software-engineering skills in addition to a research background.</li>\n</ul>\n<p><strong>Preferred Qualifications:</strong></p>\n<ul>\n<li>Experience in reinforcement learning.</li>\n<li>Experience in post-training methods.</li>\n<li>Experience in Large Language Models for information-seeking scenarios.</li>\n</ul>\n<p>The US base salary range for this full-time position is between $147,000 USD - 211,000 + 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_c6c0a57f-a27","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/7669124","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$147,000 USD - 211,000 + bonus + equity + benefits","x-skills-required":["PhD in a relevant area","Strong software-engineering skills","Reinforcement learning","Post-training methods","Large Language Models"],"x-skills-preferred":["Experience in reinforcement learning","Experience in post-training methods","Experience in LLMs for information-seeking scenarios"],"datePosted":"2026-04-18T15:39:59.926Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View, California, US"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"PhD in a relevant area, Strong software-engineering skills, Reinforcement learning, Post-training methods, Large Language Models, Experience in reinforcement learning, Experience in post-training methods, Experience in LLMs for information-seeking scenarios","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":147000,"maxValue":211000,"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_cb2af8f9-e2d"},"title":"Senior Technical Program Manager, GeminiApp","description":"<p><strong>Role Details</strong></p>\n<p>As a Senior Technical Program Manager in the GeminiApp team, you will drive our organisation-wide and cross-product area initiatives that change the trajectory of our business and product.</p>\n<p><strong>Key Responsibilities</strong></p>\n<ul>\n<li>Translate ambiguous, open-ended business priorities into structured and executable programs.</li>\n<li>Proactively identify and mitigate risks, implementing solutions to keep projects on velocity.</li>\n<li>Mechanize critical parts of the business to generate predictable outputs.</li>\n<li>Spearhead critical programs, driving progress from conception to delivery.</li>\n<li>Forge close partnerships with PM and Engineering leads to define product strategy and ensure precise execution.</li>\n<li>Navigate and resolve complex dependencies across diverse workstreams, functions, and organisations.</li>\n<li>Deliver clear, consistent updates on progress, risks, and plans to senior leadership.</li>\n<li>Excel at managing multiple, time-sensitive projects concurrently.</li>\n<li>Guide cross-functional teams in identifying, prioritising, and tracking tasks to meet key deadlines.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Bachelor&#39;s degree in a technical field, or equivalent practical experience.</li>\n<li>10+ years of experience in technical program management or engineering management.</li>\n<li>Track record of disambiguating and delivering repeatable business value.</li>\n<li>Track record of fast-paced, high-volume, and cutting-edge consumer software.</li>\n<li>Proven track record of collaborating with and influencing stakeholders across various functions and sites, especially in situations with little authority and considerable ambiguity.</li>\n<li>Exceptional communication, writing, and presentation skills.</li>\n</ul>\n<p><strong>Preferred Qualifications</strong></p>\n<ul>\n<li>Experience working delivering products that leverage large language models as part of primary experience.</li>\n<li>Experience in hardware and software development life-cycles, metric definition and executive presentation, and technical program management.</li>\n<li>Extensive experience in capacity and resource planning.</li>\n<li>Experience in implementing process improvement methodologies to drive efficiency and scale across multiple teams.</li>\n<li>Experience with motivating teams and individuals to change as the business environment changes.</li>\n<li>Ability to lead and inspire geographically dispersed teams, build strong relationships, and collaborate with stakeholders at all levels.</li>\n<li>Excellent strategic thinking and planning skills, with the ability to translate business objectives into initiatives and execute on them.</li>\n</ul>\n<p><strong>Salary</strong></p>\n<p>The US base salary range for this full-time position is between $227,000 USD - 320,000 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_cb2af8f9-e2d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"GeminiApp","sameAs":"https://deepmind.com/","logo":"https://logos.yubhub.co/deepmind.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/deepmind/jobs/7488187","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$227,000 USD - 320,000 USD + bonus + equity + benefits","x-skills-required":["Technical Program Management","Engineering Management","Disambiguating Business Priorities","Risk Mitigation","Project Management","Communication","Writing","Presentation"],"x-skills-preferred":["Large Language Models","Hardware and Software Development Life-Cycles","Metric Definition and Executive Presentation","Capacity and Resource Planning","Process Improvement Methodologies","Team Motivation","Geographically Dispersed Teams","Strategic Thinking and Planning"],"datePosted":"2026-04-18T15:39:28.825Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View, California, US"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Technical Program Management, Engineering Management, Disambiguating Business Priorities, Risk Mitigation, Project Management, Communication, Writing, Presentation, Large Language Models, Hardware and Software Development Life-Cycles, Metric Definition and Executive Presentation, Capacity and Resource Planning, Process Improvement Methodologies, Team Motivation, Geographically Dispersed Teams, Strategic Thinking and Planning","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":227000,"maxValue":320000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f4bfc542-67c"},"title":"Applied AI Engineer","description":"<p>As an Applied AI Engineer at Anthropic, you will guide customers from technical discovery through successful deployment of our AI models. You will combine deep engineering expertise with customer-facing skills to help customers understand the potential of working with Large Language Models (LLMs) and build innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Serve as a technical advisor to Anthropic customers as they deploy new products &amp; workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success</li>\n<li>Partner with account executives to deeply understand customer product requirements and architect technical solutions, ensuring alignment between business objectives and technical implementation</li>\n<li>Guide technical architecture decisions and help customers build state-of-the-art products &amp; workflows with LLMs via API</li>\n<li>Develop customized pilots, prototypes, and evaluation suites that make the case for customer deployment of our models into customer products and workflows via our API</li>\n<li>Lead hands-on technical workshops and code reviews with customer engineering teams</li>\n<li>Identify common design patterns and contribute insights back to our Product and Engineering teams</li>\n<li>Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks</li>\n<li>Travel occasionally to customer sites for workshops, implementation support, and building relationships</li>\n<li>Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>4+ years of experience in a technical role such as Customer Engineer, Forward Deployed Engineer, Software Engineer or Technical Product Manager with a desire to work closely with customers</li>\n<li>Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale</li>\n<li>Strong programming skills with proficiency in Python and experience building production applications</li>\n<li>Expertise working with common LLM implementation patterns, prompt engineering, evaluation frameworks, agent frameworks, and retrieval frameworks.</li>\n<li>Ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems</li>\n<li>High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity</li>\n<li>Passion for advancing safe, beneficial AI systems through creative technical applications</li>\n<li>Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach</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_f4bfc542-67c","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5055488008","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","Large Language Models (LLMs)","API","Technical Architecture","Customer Success","Account Management","Technical Workshops","Code Reviews","Design Patterns","AI Product Development"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:39:14.191Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Tokyo, Japan"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Large Language Models (LLMs), API, Technical Architecture, Customer Success, Account Management, Technical Workshops, Code Reviews, Design Patterns, AI Product Development"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d1c3717f-844"},"title":"Biological Safety Research Scientist","description":"<p>We are seeking a Biological Safety Research Scientist to join our Safeguards team. As a member of this team, you will apply your technical skills to design and develop safety systems that detect harmful behaviors and prevent misuse by sophisticated threat actors. You will be at the forefront of defining what responsible AI safety looks like in the biological domain, working across research, policy, and engineering to translate complex biosecurity concepts into concrete technical safeguards.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Design and execute capability evaluations to assess the capabilities of new models</li>\n<li>Collaborate closely with internal and external threat modeling experts to develop training data for our safety systems, and with ML engineers to train these safety systems, optimizing for both robustness against adversarial attacks and low false-positive rates for legitimate researchers</li>\n<li>Analyze safety system performance in traffic, identifying gaps and proposing improvements</li>\n<li>Develop rigorous stress-testing of our safeguards against evolving threats and product surfaces</li>\n<li>Partner with Research, Product, and Policy teams to ensure biological safety is embedded throughout the model development lifecycle</li>\n<li>Contribute to external communications, including model cards, blog posts, and policy documents related to biological safety</li>\n<li>Monitor emerging technologies for their potential to contribute to new risks and new mitigation strategies, and strategically address these</li>\n</ul>\n<p>You may be a good fit for this role if you have a PhD in molecular biology, virology, microbiology, biochemistry, systems or computational biology, or a related life sciences field, or equivalent professional experience. You should also have extensive experience in scientific computing and data analysis, with proficiency in programming (Python preferred), deep expertise in modern biology, including both &#39;reading&#39; and &#39;writing&#39; techniques in biology, familiarity with dual-use research concerns, select agent regulations, and biosecurity frameworks, strong analytical and writing skills, and a passion for learning new skills and adapting to changing techniques and technologies.</p>\n<p>Preferred qualifications include background in AI/ML systems, particularly experience with large language models, experience in developing ML for biological systems, and extensive experience in complex projects with multiple stakeholders.</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_d1c3717f-844","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5066977008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$300,000-$320,000 USD","x-skills-required":["PhD in molecular biology, virology, microbiology, biochemistry, systems or computational biology, or a related life sciences field","Extensive experience in scientific computing and data analysis","Proficiency in programming (Python preferred)","Deep expertise in modern biology","Familiarity with dual-use research concerns, select agent regulations, and biosecurity frameworks"],"x-skills-preferred":["Background in AI/ML systems","Experience with large language models","Experience in developing ML for biological systems","Extensive experience in complex projects with multiple stakeholders"],"datePosted":"2026-04-18T15:38:51.239Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"PhD in molecular biology, virology, microbiology, biochemistry, systems or computational biology, or a related life sciences field, Extensive experience in scientific computing and data analysis, Proficiency in programming (Python preferred), Deep expertise in modern biology, Familiarity with dual-use research concerns, select agent regulations, and biosecurity frameworks, Background in AI/ML systems, Experience with large language models, Experience in developing ML for biological systems, Extensive experience in complex projects with multiple stakeholders","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":300000,"maxValue":320000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_4114e8e4-85a"},"title":"Staff Model UX Designer, Personalization, GeminiApp","description":"<p><strong>Snapshot</strong></p>\n<p>We&#39;re hiring a Staff Model UX Designer to play a critical role in our Personalization initiatives. You&#39;ll be responsible for developing and implementing content and model behavior standards, architecting scalable frameworks and processes.</p>\n<p><strong>Responsibilities</strong></p>\n<p>Set the quality bar by creating principles, response strategies, and examples that define what good looks like. Establish comprehensive content standards and specifications for Gemini models, addressing factors like factual accuracy, privacy, safety, personality, tone, and style.</p>\n<p>Drive continuous model improvement by diagnosing quality gaps and developing scalable, strategic frameworks,including guidelines, technical instructions, and cross-functional alignment,needed to scale response excellence.</p>\n<p>Partner closely with cross-functional teams, including engineers, product managers, researchers, and data scientists to shape the behavior of LLM models in support of growth strategies.</p>\n<p>Understand users and advocate for a user-centered approach to model output, ensuring that the content the model generates meets the needs and expectations of our users.</p>\n<p>Deeply understand model training methods and processes, and stay up-to-date on the latest advancements in generative AI.</p>\n<p><strong>About You</strong></p>\n<p>We’re looking for a systems thinker with strong skills in content strategy, conversation design, and problem-solving, anchored by a passion for the craft of writing. You’ll have experience developing guidelines, exemplary content, evaluations, and rubrics for LLMs, as well as writing and editing in a fast-paced, agile environment.</p>\n<p>Leveraging complex cross-functional partnerships, you’ll work with product, engineering, research, and data science to articulate and guide product strategy.</p>\n<p>To set you up for success as a UX Content Designer at Google DeepMind, we look for the following skills and experience:</p>\n<ul>\n<li>Demonstrated Strategic Impact &amp; Leadership: Experience shaping content for strategic initiatives in relevant areas, such as hardware, software, digital agencies, creative industries, or journalism.</li>\n</ul>\n<ul>\n<li>Mastery of Writing Craft &amp; Execution: A portfolio of work demonstrating intuitive, systems-aware content solutions with exceptional craft and strong rigor. Recognized as a &quot;go-to&quot; expert, sharing knowledge and elevating team skill.</li>\n</ul>\n<ul>\n<li>Adaptability: Thrives in complexity, continuously learning and adapting with a growth mindset. Evolves strategies and processes as needed.</li>\n</ul>\n<ul>\n<li>Fluency in AI product design process: Experience training and tuning large language models or other generative AI technologies. Experience gathering and working with data to identify loss patterns and create actionable insights</li>\n</ul>\n<p>In addition, the following would be an advantage:</p>\n<ul>\n<li>Growth and discovery expertise: experience in driving successful growth and discovery initiatives for digital products.</li>\n</ul>\n<ul>\n<li>AI Prototyping: ability to build functioning prototypes to demonstrate ideas and drive cross-functional alignment.</li>\n</ul>\n<p><strong>Salary</strong></p>\n<p>The US base salary range for this full-time position is between $165,000 USD - $245,000 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_4114e8e4-85a","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/7793421","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$165,000 USD - $245,000 USD + bonus + equity + benefits","x-skills-required":["Content strategy","Conversation design","Problem-solving","Writing and editing","Large language models","Generative AI","Data analysis","Cross-functional collaboration"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:38:29.098Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View, California, US; New York City, New York, US; Seattle, Washington, US"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Content strategy, Conversation design, Problem-solving, Writing and editing, Large language models, Generative AI, Data analysis, Cross-functional collaboration","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":165000,"maxValue":245000,"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_c319dc13-e7d"},"title":"Head of Partner Success","description":"<p><strong>About the role\\n\\nYou will build Partner Success at Anthropic from scratch. This means hiring your first partner success managers, defining how they run their portfolios, and personally carrying a portfolio of partners yourself as your reference implementation.\\n\\nYou&#39;ll be the standard for what good looks like before you ask anyone else to do it. You will also define which partners get the team&#39;s attention. Far more firms want to be a managed partner than your team could ever serve, and choosing the right ones is one of the most consequential decisions in this role.\\n\\n## Responsibilities:\\n\\n- Build and lead the Partner Success team from scratch. Hire your first partner success managers, define how they run their portfolios, and build the operating system the team inherits.\\n\\n- Personally carry a portfolio of managed partners as your reference implementation. Be the standard for what good looks like before asking anyone else to do it.\\n\\n- Decide which partners get the team&#39;s attention. Design the criteria for entry into and graduation from the managed portfolio, and reshape it as the data comes in.\\n\\n- Design the team&#39;s engagement model. Define when proactive engagement is warranted, when reactive engagement is triggered by clear signals, and when partners are better served by routing, programmatic enablement, and the certified bench.\\n\\n- Run the joint planning and business review cadence with each managed partner. Quarterly business reviews with alliance and practice leads. Joint goal-setting on customer adoption, certified architects, references, and industry positioning.\\n\\n- Drive scalable enablement across the managed partner book. Make sure partner architects are trained on new Claude capabilities as they ship, the partner&#39;s offerings reflect what Claude can now do, and the partner&#39;s bench is positioned to apply new features in their customer work at scale.\\n\\n- Drive adoption, retention, and expansion in the joint customer book. Track the health of the customer accounts each partner is serving on Claude, surface stalls early, bring the right people in to unblock, and turn at-risk accounts around.\\n\\n- Drive industry specialization across the managed partner book. Coach each partner to commit to one or more industry lanes and hold them to building real bench depth and published reference work in those lanes.\\n\\n- Steward co-investment funding decisions. Own the calls on where Anthropic puts co-investment dollars to back specific partner-led customer engagements. The bar is outcomes, not consultant hours.\\n\\n- Interlock with Anthropic&#39;s direct sales field and with the alliances organization that owns the executive relationship with each strategic partner. Define the handoffs in writing, train both sides, and hold the line.\\n\\n- Define the team&#39;s regional coverage model as the portfolio grows and hire accordingly.\\n\\n- Instrument the managed partner portfolio. Consumption growth by partner, sourced and influenced pipeline, time-to-first-deal, adoption-retention-expansion trends, and partner health trajectory.\\n\\n## You may be a good fit if you have:\\n\\n- Six to ten years of experience working with consulting and systems integration partners at a software company, cloud platform, or partner-led business, with at least two of those years managing a team.\\n\\n- Built or scaled a partner-facing team from scratch before , hiring, onboarding, methodology creation , not just managed an existing team.\\n\\n- Deep understanding of how partner success works in a usage-based business. You have held a number tied to customer behavior (adoption, retention, expansion) rather than contract signature.\\n\\n- Strong commercial instincts on partner selection and co-investment funding. You can tell which partners are worth investing in and which look impressive on paper but will not ship customer outcomes.\\n\\n- Experience running scalable partner or practitioner enablement, or the hunger to learn it. You understand the difference between a training program that gets attendance and one that changes what practitioners do in customer engagements the next week.\\n\\n- Enough technical fluency to be credible in an architecture review. You do not need to write code, but you can follow the conversation and ask the second question when a partner architect walks through how they are using Claude on a real customer problem.\\n\\n- Comfortable sharing the partner relationship with a separate alliances team that owns the executive conversation. You can work closely with them, weekly, without ego friction.\\n\\n- Use Claude or another large language model in your own daily work , not as a chat tool, but as part of how you prepare for partner reviews, draft account plans, analyze pipeline, and coach your team. We will ask you to walk us through a recent deliverable.\\n\\n## Strong candidates may also have:\\n\\n- Direct experience with global systems integrators such as Accenture, Deloitte, Capgemini, Infosys, TCS, or Wipro, and an understanding of how their delivery practices are built.\\n\\n- Working at a company in transition from product-led to partner-led motion.\\n\\n- Stewarding co-investment funding at scale and forming opinions about what works and what does not.\\n\\n- Building a vertical industry motion in which partners specialized by industry and the program rewarded it.\\n\\n- Designing an engagement model for a small team covering a large ecosystem , the proactive-reactive-automated split that lets a handful of people serve thousands of relationships.\\n\\nThe annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\\n\\nAnnual Salary: $300,000-$355,000 USD</strong></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_c319dc13-e7d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.co/","logo":"https://logos.yubhub.co/anthropic.co.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5182866008","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$300,000-$355,000 USD","x-skills-required":["partner success","partner management","team leadership","commercial instincts","co-investment funding","scalable enablement","adoption","retention","expansion","industry specialization","stewarding co-investment funding"],"x-skills-preferred":["Claude","large language model","architecture review","global systems integrators","product-led to partner-led motion","co-investment funding at scale","vertical industry motion","engagement model design"],"datePosted":"2026-04-18T15:38:06.173Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Sales","industry":"Technology","skills":"partner success, partner management, team leadership, commercial instincts, co-investment funding, scalable enablement, adoption, retention, expansion, industry specialization, stewarding co-investment funding, Claude, large language model, architecture review, global systems integrators, product-led to partner-led motion, co-investment funding at scale, vertical industry motion, engagement model design","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":300000,"maxValue":355000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f77be5b8-7b6"},"title":"Finance Expert - Risk","description":"<p>As a Finance Risk Expert at xAI, you will play a crucial role in advancing our cutting-edge AI systems by providing high-quality annotations, expert evaluations, and detailed risk reasoning using specialized labeling tools.</p>\n<p>You will collaborate closely with technical teams to support the development and refinement of new AI capabilities, with a primary focus on quantitative financial risk management domains. Your expertise will drive the selection and rigorous resolution of complex risk-related problems, including market risk modeling, credit and counterparty risk, liquidity and funding risk, operational and model risk, stress testing &amp; scenario analysis, Value at Risk (VaR)/Expected Shortfall (ES), risk attribution, capital allocation (economic/regulatory), and enterprise-wide risk frameworks under regulatory regimes (Basel, Dodd-Frank, IFRS 9, etc.).</p>\n<p>This role requires exceptional quantitative rigor, rapid adaptation to evolving guidelines, and the ability to deliver precise, technically sound critiques, derivations, and solutions in a fast-paced environment. As a Finance Risk Expert, you will directly support xAI&#39;s mission by helping train and refine frontier AI models. You will teach the models how risk professionals quantify uncertainties, model tail events, assess portfolio vulnerabilities, ensure regulatory compliance, perform stress testing, and make data-driven decisions to protect capital and maintain financial stability.</p>\n<p>Your tasks may include recording audio walkthroughs of risk models, participating in video-based scenario reasoning, or producing detailed quantitative risk analysis traces. All outputs are considered work-for-hire and owned by xAI.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Use proprietary annotation and evaluation software to deliver accurate labels, rankings, critiques, and comprehensive solutions on assigned projects</li>\n<li>Consistently produce high-quality, curated data that adheres to strict quantitative and regulatory standards</li>\n<li>Collaborate with engineers and researchers to develop and iterate on new training tasks, risk-specific benchmarks, and evaluation frameworks</li>\n<li>Provide constructive feedback to improve the efficiency, precision, and usability of annotation and data-collection tools</li>\n<li>Select and solve challenging problems from financial risk domains where you have deep expertise</li>\n</ul>\n<p>Basic Qualifications:</p>\n<ul>\n<li>Master’s or PhD in a quantitative discipline: Quantitative Finance, Financial Engineering, Financial Mathematics, Statistics, Applied Mathematics, Econometrics, Risk Management, Operations Research, Physics, Computer Science (with risk/finance focus), or closely related field or equivalent professional experience as a quantitative risk analyst, risk modeler, or risk quant</li>\n<li>Excellent written and verbal English communication (technical reports, regulatory documentation, explanatory breakdowns)</li>\n<li>Strong familiarity with financial risk data sources and platforms (Bloomberg, Refinitiv, Moody’s Analytics, S&amp;P Capital IQ, RiskMetrics, internal bank risk systems, regulatory filings, Basel/FRB datasets, etc.)</li>\n<li>Exceptional analytical reasoning, attention to detail, and ability to exercise sound judgment with incomplete or ambiguous data</li>\n</ul>\n<p>Preferred Skills and Experience:</p>\n<ul>\n<li>Professional experience in quantitative risk management, model development/validation, or risk analytics at a bank, hedge fund, asset manager, insurance company, regulator, or consulting firm</li>\n<li>Track record of publication(s) or contributions in refereed journals/conferences on risk, econometrics, statistics, or quantitative finance</li>\n<li>Prior teaching, mentoring, or training experience (university, industry workshops, regulatory training)</li>\n<li>Proficiency in Python/R for risk modeling (pandas, NumPy, SciPy, statsmodels, QuantLib, PyTorch/TensorFlow for ML risk models, etc.) and familiarity with risk systems (Murex, Calypso, Numerix, etc.)</li>\n<li>Experience with Monte Carlo simulation, copula models, stochastic processes, time-series analysis, extreme value theory, or machine learning for risk (anomaly detection, credit scoring, etc.)</li>\n<li>Knowledge of regulatory capital frameworks (Basel III/IV, FRB CCAR, SR 11-7 model risk guidance, IFRS 9/CECL, Solvency II)</li>\n<li>CFA, FRM, PRM, CQF, or similar risk-focused certifications</li>\n<li>Previous exposure to large language models, AI safety, or quantitative evaluation pipelines</li>\n</ul>\n<p>Location and Other Expectations:</p>\n<ul>\n<li>Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit</li>\n<li>For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required</li>\n<li>Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs</li>\n<li>For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time</li>\n<li>We are unable to provide visa sponsorship</li>\n<li>For those who will be working from a personal device, your computer must meet xAI’s minimum hardware requirements</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a 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pipelines"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b47fc91b-597"},"title":"Anthropic Fellows Program — ML Systems & Performance","description":"<p>The Anthropic Fellows Program is a 4-month full-time research opportunity designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent, regardless of previous experience. Fellows will primarily use external infrastructure to work on an empirical project aligned with our research priorities, with the goal of producing a public output. In one of our earlier cohorts, over 80% of fellows produced papers.</p>\n<p>We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in July 2026 and beyond.</p>\n<p>As a Fellow, you will receive:</p>\n<ul>\n<li>Direct mentorship from Anthropic researchers</li>\n<li>Access to a shared workspace in either Berkeley, California or London, UK</li>\n<li>Connection to the broader AI safety and security research community</li>\n<li>A weekly stipend of $3,850 USD / £2,310 GBP / $4,300 CAD, plus benefits</li>\n<li>Funding for compute and other research expenses</li>\n</ul>\n<p>The interview process will include an initial application and reference check, technical assessments and interviews, and a research discussion.</p>\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>The expected base stipend for this role is $3,850 USD / £2,310 GBP / $4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension).</p>\n<p>Fellows will undergo a project selection and mentor matching process. Potential mentors include Alwin Peng and Zygi Straznickas. For a past example of an engineering-heavy project, see &#39;AI agents find $4.6M in blockchain smart contract exploits&#39;.</p>\n<p>Projects in this workstream may include building a CPU simulator for accelerator workloads, adding backends for different accelerators on an open source project, building on demand infrastructure for other infrastructure heavy fellows projects, and building complex synthetic data or environment pipelines.</p>\n<p>To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program. Workspace locations are in London and Berkeley, and we are open to remote fellows in the UK, US, or Canada.</p>\n<p>We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organisations.</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_b47fc91b-597","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5183051008","x-work-arrangement":"remote","x-experience-level":"entry","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python programming","Software engineering","Complex ML systems","Distributed systems","High-performance computing","Training, fine-tuning, or evaluating large language models","Analyzing and debugging model training processes"],"x-skills-preferred":["Experience with training, fine-tuning, or evaluating large language models","Adept at analyzing and debugging model training processes","Strong background in a discipline relevant to a specific Fellows workstream","Experience in areas of research or engineering related to their workstream"],"datePosted":"2026-04-18T15:34:47.218Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK; Ontario, CAN; Remote-Friendly, United States; San Francisco, CA"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python programming, Software engineering, Complex ML systems, Distributed systems, High-performance computing, Training, fine-tuning, or evaluating large language models, Analyzing and debugging model training processes, Experience with training, fine-tuning, or evaluating large language models, Adept at analyzing and debugging model training processes, Strong background in a discipline relevant to a specific Fellows workstream, Experience in areas of research or engineering related to their workstream"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f578503a-af9"},"title":"Senior Analyst - Safety Operations (CSE)","description":"<p>We are seeking a Senior Analyst - Safety Operations (CSE) to join our team. As a Senior Analyst, you will play a critical role in ensuring the safety and integrity of our AI systems. Your primary responsibilities will include processing appeals, auditing automations, and labeling use cases in our system. You will also provide labels, annotations, and inputs on projects involving safety protocols, risk scenarios, and policy compliance. Additionally, you will collaborate with team members to provide feedback on tasks that improve AI&#39;s defenses to detect illegal and unethical behavior, as well as align Grok with our rules enforcement.</p>\n<p>To be successful in this role, you will need expertise in improving Large Language Models (LLMs), specifically related to CSE, to maximize efficiencies in enforcement and support. You will also need to have a proven expertise in identifying, mitigating, and preventing Child Sexual Abuse Material (CSAM) and Child Sexual Exploitation (CSE), including grooming behaviors and risks in AI-generated content, with strong knowledge of relevant legal obligations (such as NCMEC reporting) and industry standards for protecting minors.</p>\n<p>You will also have experience in online safety and reducing harm to protect our users and preserve Free Speech in the global public square. You will be able to interpret and apply xAI safety policies effectively, and have strong skills in ethical reasoning and risk assessment. You will also have a strong ability to utilize resources, guidelines, and frameworks for accurate safety-focused actions and escalations.</p>\n<p>In addition, you will have strong communication, interpersonal, analytical, and ethical decision-making skills. You will be committed to continuous improvement of processes to prioritize safety and risk mitigation. You will also have expertise in data analysis to identify emerging abuse vectors, uncover opportunities for operational efficiencies, and design automations that strengthen enforcement effectiveness and platform safety.</p>\n<p>Preferred qualifications include experience working in a Trust and Safety for a social media company, leveraging AI or other automation tools. You will also have experience collaborating with child safety organizations (such as NCMEC) and utilizing specialized detection tools or developing classifiers for CSAM/CSE in social media or generative AI platforms. Additionally, you will have expertise in red-teaming and adversarial testing of Large Language Models to proactively identify novel abuse vectors, jailbreaks, and safety failure modes, with a proven ability to translate findings into concrete improvements for enforcement systems and platform robustness.</p>\n<p>This role may involve exposure to sensitive or graphic content, including vulgar language, violent threats, pornography, and other graphic images.</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_f578503a-af9","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/5097904007","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$43.75 - $62.50 USD hourly","x-skills-required":["Improving Large Language Models (LLMs)","Child Sexual Abuse Material (CSAM) and Child Sexual Exploitation (CSE)","Online safety and reducing harm","Ethical reasoning and risk assessment","Data analysis"],"x-skills-preferred":["Experience working in a Trust and Safety for a social media company","Collaborating with child safety organizations","Red-teaming and adversarial testing of Large Language Models"],"datePosted":"2026-04-18T15:25:26.718Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Palo Alto, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Improving Large Language Models (LLMs), Child Sexual Abuse Material (CSAM) and Child Sexual Exploitation (CSE), Online safety and reducing harm, Ethical reasoning and risk assessment, Data analysis, Experience working in a Trust and Safety for a social media company, Collaborating with child safety organizations, Red-teaming and adversarial testing of Large Language Models"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2f818897-404"},"title":"Senior Analyst - Safety Operations (CSE)","description":"<p><strong>About the Role</strong></p>\n<p>xAI is seeking a Senior Analyst - Safety Operations (CSE) to join our team. As a Senior Analyst, you will play a critical role in ensuring the safety and integrity of our AI systems.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Process appeals, audit automations, and properly label use cases in the system.</li>\n<li>Provide labels, annotations, and inputs on projects involving safety protocols, risk scenarios, and policy compliance.</li>\n<li>Support the delivery of high-quality curated data that reinforces xAI&#39;s rules and ethical alignment.</li>\n<li>Collaborate with team members to provide feedback on tasks that improve AI&#39;s defenses to detect illegal and unethical behavior, as well as align Grok with our rules enforcement.</li>\n</ul>\n<p><strong>Basic Qualifications</strong></p>\n<ul>\n<li>Expertise in improving Large Language Models (LLMs), specifically related to CSE, to maximize efficiencies in enforcement and support and ability to propose solutions to increase security and safety of our platform.</li>\n<li>Proven expertise in identifying, mitigating, and preventing Child Sexual Abuse Material (CSAM) and Child Sexual Exploitation (CSE), including grooming behaviors and risks in AI-generated content, with strong knowledge of relevant legal obligations (such as NCMEC reporting) and industry standards for protecting minors.</li>\n<li>Proven experience in online safety and reducing harm to protect our users and preserve Free Speech in the global public square.</li>\n<li>Ability to interpret and apply xAI safety policies effectively.</li>\n<li>Proficiency in analyzing complex scenarios, with strong skills in ethical reasoning and risk assessment.</li>\n<li>Strong ability to utilize resources, guidelines, and frameworks for accurate safety-focused actions and escalations.</li>\n<li>Strong communication, interpersonal, analytical, and ethical decision-making skills.</li>\n<li>Commitment to continuous improvement of processes to prioritize safety and risk mitigation.</li>\n<li>Expertise in data analysis to identify emerging abuse vectors, uncover opportunities for operational efficiencies, and design automations that strengthen enforcement effectiveness and platform safety.</li>\n</ul>\n<p><strong>Preferred Skills and Experience</strong></p>\n<ul>\n<li>Experience working in a Trust and Safety for a social media company, leveraging AI or other automation tools.</li>\n<li>Experience collaborating with child safety organizations (such as NCMEC) and utilizing specialized detection tools or developing classifiers for CSAM/CSE in social media or generative AI platforms.</li>\n<li>Expertise in red-teaming and adversarial testing of Large Language Models to proactively identify novel abuse vectors, jailbreaks, and safety failure modes, with a proven ability to translate findings into concrete improvements for enforcement systems and platform robustness.</li>\n</ul>\n<p>This role may involve exposure to sensitive or graphic content, including vulgar language, violent threats, pornography, and other graphic images.</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_2f818897-404","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/5097907007","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Large Language Models (LLMs)","Child Sexual Abuse Material (CSAM)","Child Sexual Exploitation (CSE)","Online safety","Risk assessment","Ethical reasoning","Data analysis","Automation tools","Social media","Generative AI"],"x-skills-preferred":["Red-teaming","Adversarial testing","Trust and Safety","Child safety organizations","Specialized detection tools","Classifier development"],"datePosted":"2026-04-18T15:25:17.446Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bastrop, TX"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Large Language Models (LLMs), Child Sexual Abuse Material (CSAM), Child Sexual Exploitation (CSE), Online safety, Risk assessment, Ethical reasoning, Data analysis, Automation tools, Social media, Generative AI, Red-teaming, Adversarial testing, Trust and Safety, Child safety organizations, Specialized detection tools, Classifier development"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f1981394-2ef"},"title":"Senior Analyst, Safety Operations","description":"<p>About xAI</p>\n<p>xAI&#39;s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge.</p>\n<p><strong>RESPONSIBILITIES:</strong></p>\n<ul>\n<li>Process appeals, audit automations, and label use cases in the system.</li>\n</ul>\n<ul>\n<li>Provide labels, annotations, and inputs on projects involving safety protocols, risk scenarios, and policy compliance.</li>\n</ul>\n<ul>\n<li>Support the delivery of high-quality curated data that reinforces xAI&#39;s rules and ethical alignment.</li>\n</ul>\n<ul>\n<li>Collaborate with team members to provide feedback on tasks that improve AI&#39;s defenses to detect illegal and unethical behaviour, as well as align Grok with our rules enforcement.</li>\n</ul>\n<p><strong>BASIC QUALIFICATIONS:</strong></p>\n<ul>\n<li>Expertise in improving Large Language Models (LLMs) to maximise efficiencies in enforcement and support and ability to propose solutions to increase security and safety of our platform.</li>\n</ul>\n<ul>\n<li>Proven experience in online safety and reducing harm to protect our users and preserve Free Speech in the 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You will be expected to have strong communication skills, be able to concisely and accurately share knowledge with your teammates, and demonstrate initiative and leadership.</p>\n<p>The base salary for this position is $180,000 - $440,000 USD, and we offer a comprehensive total rewards package including equity, medical, vision, and dental coverage, access to a 401(k) retirement plan, short &amp; long-term disability insurance, life insurance, and various other discounts and perks.</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_47f1040a-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/4378344007","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$180,000 - $440,000 USD","x-skills-required":["configuring and troubleshooting complex distributed data processing systems","building bespoke data processing systems from scratch","preparing pre-training and post-training data for state-of-the-art large language models and generative models","organising and meticulously bookkeeping data across multiple clouds, modalities, and sources"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:23:12.460Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Palo Alto, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"configuring and troubleshooting complex distributed data processing systems, building bespoke data processing systems from scratch, preparing pre-training and post-training data for state-of-the-art large language models and generative models, organising and meticulously bookkeeping data across multiple clouds, modalities, and sources","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_baec12df-551"},"title":"Technical Marketing Engineer","description":"<p>About Mistral AI</p>\n<p>At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.</p>\n<p>We are a distributed team with offices in France, USA, UK, Germany, and Singapore. We are a low-ego and team-spirited organisation.</p>\n<p>About the Role</p>\n<p>As a Technical Marketing Engineer (TME), you will bridge the gap between Mistral AI&#39;s science/engineering organisations and our marketing teams. You will create technical content to educate enterprise decision-makers, align technical capabilities with business goals, and accelerate sales cycles.</p>\n<p>Responsibilities</p>\n<ul>\n<li>Create and Deliver Technical Content: Develop model/product technical launch materials, technical proof points, presentation decks, demo videos, webinars, workshops, blogs, whitepapers, and sales training materials.</li>\n<li>Enable Sales and Partners: Equip sales teams and partners with technical knowledge to engage in deeper, more credible conversations with technical stakeholders.</li>\n<li>Support Model Launches: Collaborate on model launches, ensuring technical messaging is clear and impactful.</li>\n<li>Engage with Analysts and Industry Leaders: Participate in analyst briefings, technical advisory boards (TABs), and industry standards discussions to position Mistral AI as a thought leader.</li>\n<li>Build Trust and Drive Adoption: Work with solutions architects and developer relations to ensure seamless integration and implementation of our solutions through targeted technical content.</li>\n<li>Interface with Science and Engineering: Act as the technical liaison between engineering, science, and marketing teams, translating complex LLM concepts (including pre-training and post-training techniques) into actionable insights for enterprise audiences.</li>\n</ul>\n<p>Who You Are</p>\n<ul>\n<li>Experience: 3+ years in technical marketing, solutions engineering, or a similar role, preferably in AI/ML or enterprise software.</li>\n<li>Technical Skills: Ability to understand and communicate complex technical concepts to both technical and non-technical audiences. Familiarity with enterprise AI solutions, cloud environments, and technical sales enablement.</li>\n<li>Mindset: Collaborative, creative, and low-ego. Passionate about AI and its potential to transform industries.</li>\n</ul>\n<p>What We Offer</p>\n<ul>\n<li>Competitive cash salary and equity</li>\n<li>Daily lunch vouchers: Swile meal vouchers with 10,83€ per worked day, incl 60% offered by company</li>\n<li>Sport: Enjoy discounted access to gyms and fitness studios through our Wellpass partnership</li>\n<li>Transportation: Monthly contribution to a mobility pass via Betterway</li>\n<li>Health: Full health insurance for you and your family</li>\n<li>Parental: Generous parental leave policy</li>\n<li>Visa sponsorship</li>\n<li>Coaching: we offer BetterUp coaching on a voluntary basis</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_baec12df-551","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral AI","sameAs":"https://mistral.ai","logo":"https://logos.yubhub.co/mistral.ai.png"},"x-apply-url":"https://jobs.lever.co/mistral/942f8627-3079-416b-a2a7-bf651b336acb","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Ability to understand and communicate complex technical concepts to both technical and non-technical audiences","Familiarity with enterprise AI solutions, cloud environments, and technical sales enablement","Large language models (LLMs), including pre-training and post-training techniques","AI/ML or enterprise software","Technical marketing, solutions engineering, or a similar role"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:48:12.511Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Ability to understand and communicate complex technical concepts to both technical and non-technical audiences, Familiarity with enterprise AI solutions, cloud environments, and technical sales enablement, Large language models (LLMs), including pre-training and post-training techniques, AI/ML or enterprise software, Technical marketing, solutions engineering, or a similar role"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b3289639-f91"},"title":"Machine Learning Engineer, Open-Source Software","description":"<p>About Mistral AI</p>\n<p>We believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.</p>\n<p>Role Summary</p>\n<p>You will be in charge of open-sourcing state-of-the-art models, whilst maintaining and improving Mistral’s publicly available libraries. Your work is critical in helping turn research breakthroughs into tangible solutions and improve Mistral&#39;s open-source ecosystem.</p>\n<p>Responsibilities</p>\n<p>• Releasing our models to open-source platforms and libraries, e.g., vLLM, GitHub, Hugging Face\n• Maintaining Mistral’s open-source libraries (mistral-common, mistral-finetune, mistral-inference)\n• Create and maintain tooling and services: both internal facing (internal research) and external facing (open-source libraries)\n• Implement and optimize open-source and internal libraries for performance and accuracy, ensuring production readiness and employing cutting-edge technology and innovative approaches\n• Collaborate with the open-source community (PyTorch, vLLM, Hugging Face)</p>\n<p>About You</p>\n<p>• Master’s degree in Computer Science, Machine Learning, Data Science, or a related field\n• Experience contributing to popular open-source libraries such as PyTorch, Tensorflow, JAX, vLLM, Transformers, Llama.cpp, ...\n• Passion for contributing to the open-source software ecosystem\n• Expert programming skills in Python, PyTorch, MLOps\n• Adaptable, proactive, and autonomous\n• Attention to detail and a drive to go the last mile to build almost perfect tools\n• Deep understanding of machine learning approaches, especially LLMs and algorithms\n• Low-ego, collaborative and have a real team player mindset</p>\n<p>Now, it would be ideal if you have:</p>\n<p>• Experience with training and fine-tuning large language models (e.g., distillation, supervised fine-tuning, policy optimization)\n• Experience working with Slurm\n• Worked with research teams before\n• Experience as a core-maintainer of a popular ML open-source library</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_b3289639-f91","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral AI","sameAs":"https://mistral.ai","logo":"https://logos.yubhub.co/mistral.ai.png"},"x-apply-url":"https://jobs.lever.co/mistral/ef4c26fc-3fdb-4dd2-a64e-95264ee769dd","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","PyTorch","MLOps","Open-source software development","Machine learning","Large language models","Slurm"],"x-skills-preferred":["Experience with training and fine-tuning large language models","Experience working with Slurm","Research team experience","Core-maintainer of a popular ML open-source library"],"datePosted":"2026-04-17T12:48:06.893Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, MLOps, Open-source software development, Machine learning, Large language models, Slurm, Experience with training and fine-tuning large language models, Experience working with Slurm, Research team experience, Core-maintainer of a popular ML open-source library"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d9383bcf-242"},"title":"Model Behavior Architect","description":"<p>About this role</p>\n<p>As a Model Behavior Architect at Mistral AI, you will be at the forefront of defining and measuring Large Language Model (LLM) behavior. 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whitespaces, and emerging trends enterprise product management.</p>\n</li>\n<li><p>Validate product direction: Engage directly with customers and partners to validate positioning, value propositions and feature priorities.</p>\n</li>\n</ul>\n<p>Build &amp; Ship</p>\n<ul>\n<li><p>Own the lifecycle: Drive end-to-end product development, from ideation to launch and iteration,balancing speed, quality, and user delight.</p>\n</li>\n<li><p>Champion the user: Partner with design and research to craft intuitive, high-impact and developer first experiences, using data and feedback to refine continuously.</p>\n</li>\n</ul>\n<p>Scale &amp; Execute</p>\n<ul>\n<li><p>Go-to-market: Collaborate with marketing and sales to launch products successfully, including pricing, positioning, and adoption strategies.</p>\n</li>\n<li><p>Align stakeholders: Rally science, engineering, design and business teams around priorities, trade-offs and timelines.</p>\n</li>\n<li><p>Prioritize ruthlessly: Maintain a 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This means being able to design complex software and make it usable in production</li>\n<li>You are a self-starter, autonomous and a team player</li>\n</ul>\n<p>Now, it would be ideal if</p>\n<ul>\n<li>You have hands-on experience with training large transformer models in a distributed fashion</li>\n<li>You are able to navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment</li>\n<li>You have a strong publication record in a relevant scientific domain</li>\n<li>Audio/Speech experience - audio input/out, NLP</li>\n</ul>\n<p><strong>What We Offer</strong></p>\n<ul>\n<li>Competitive salary and bonus structure</li>\n<li>Generous Equity</li>\n<li>Health: Competitive Healthcare program (Medical Provider: Blueshield of California 100% coverage for employee, 75% for dependents)</li>\n<li>Pension: 401K (6% matching)</li>\n<li>PTO: 18 days</li>\n<li>Transportation: Reimburse office parking charges, or $120/month for public transport</li>\n<li>Coaching: we offer Betterup coaching on a voluntary basis</li>\n<li>Sport: $120/month reimbursement for gym membership</li>\n<li>Meal stipend: $400 monthly allowance for meals (solution might evolve as we grow bigger)</li>\n<li>Visa sponsorship</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_fe6b2de2-36b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral","sameAs":"https://www.mistral.ai/","logo":"https://logos.yubhub.co/mistral.ai.png"},"x-apply-url":"https://jobs.lever.co/mistral/7b20d2c8-d5a7-4efd-a13e-05d920ec5985","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","PyTorch","JAX","Rust","Go","Java","Ray","Kubernetes","large language models","distributed systems","MLOps"],"x-skills-preferred":["training large transformer models","fine-tuning","evaluation and deployment","audio input/out","NLP"],"datePosted":"2026-04-17T12:45:59.717Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Palo Alto"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, JAX, Rust, Go, Java, Ray, Kubernetes, large language models, distributed systems, MLOps, training large transformer models, fine-tuning, evaluation and deployment, audio input/out, NLP"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_63887197-e18"},"title":"Senior Engineering Manager - Risk","description":"<p>Every new business that applies to Mercury is like a new star appearing in the night sky. On its own, it’s a single point of light. But when we look closer, patterns emerge,data trails from partners, filings, founders, and financial histories,all connecting to form a larger constellation.</p>\n<p>That’s what our Risk product engineering teams do at Mercury. We guide thousands of business applications through our systems,each one unique, each one needing a smooth and trustworthy landing. The challenge: keep everything moving fast without compromising safety. Every day, our work helps founders open their first account, launch their next idea, and accelerate their growth like rocketships.</p>\n<p>Our mission is to build the intelligent, automated systems and operational tools that make this possible,where machine learning, AI, and human judgment work seamlessly together to power the next generation of business banking*. We use intelligence to detect risks earlier, make real-time decisions with confidence, and enable instant, delightful account approvals that keep pace with the builders we serve.</p>\n<p>When we do it right, the result is quiet brilliance: onboarding that feels effortless, even though it’s powered by galaxies of data, precision, and care.</p>\n<p>We’re looking for a Senior Engineering Manager to lead the teams building the systems and tools that make it all happen,from application approvals to ongoing and enhanced due diligence,ensuring every business that joins Mercury is both safe and their experience is delightful.</p>\n<p>*​​Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.</p>\n<p>In this role, you will:</p>\n<ul>\n<li>Lead teams (4–8 engineers each) responsible for account onboarding, KYC/KYB, AML, and fraud detection decisioning and workflows, and operational tooling.</li>\n<li>Apply AI/ML,from traditional models to large language models,to unlock faster, real-time bank account application approvals. This work sits on the critical business path, directly driving efficiency and revenue growth.</li>\n<li>Partner with Product, Risk, and Data teams to design and deliver scalable systems that balance user experience with compliance rigor.</li>\n<li>Shape the next generation of our KYC and risk platforms,reliable, resilient, and easy to extend as regulations and business needs evolve.</li>\n<li>Create a strong culture of operational excellence, with measurable improvements to uptime, accuracy, and system quality.</li>\n<li>Build, mentor, and grow engineering talent; help managers and senior engineers level up technically and organizationally.</li>\n<li>Drive clarity amid complexity: translating between regulatory nuance and technical execution.</li>\n<li>Foster collaboration across teams to align on priorities, simplify interfaces, and make the whole system more maintainable and elegant.</li>\n</ul>\n<p>You should have:</p>\n<ul>\n<li>9+ years of software development experience, including 3–5+ years of engineering management in a high-scale tech environment.</li>\n<li>AI/ML expertise,you’ve built and launched applied AI products (from LLMs to traditional ML models), shipping them from 0→1 and scaling 1→10 in production environments.</li>\n<li>Proven success building large-scale backend distributed systems, ideally involving integrations and decision automation.</li>\n<li>Experience with or curiosity about KYC, AML, risk, or compliance systems in financial services or fintech.</li>\n<li>A track record of raising the bar for quality and reliability, balancing shipping speed with technical excellence.</li>\n<li>Strong communication and leadership skills,you can inspire engineers, partner across functions, and adapt your management style to the moment.</li>\n<li>The ability to hire, retain, and develop exceptional technical talent.</li>\n<li>A pragmatic builder’s mindset: you believe beautiful systems are those that work, adapt, and last.</li>\n</ul>\n<p>The total rewards package at Mercury includes base salary, equity (stock options/RSUs), and benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.</p>\n<p>Our target new hire base salary ranges for this role are the following:</p>\n<ul>\n<li>US employees (any location): $239,000 - $298,800</li>\n<li>Canadian employees (any location): CAD $225,900 - $282,400</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_63887197-e18","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mercury","sameAs":"https://www.mercury.com/","logo":"https://logos.yubhub.co/mercury.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/mercury/jobs/5701708004","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$239,000 - $298,800 (US) or CAD $225,900 - $282,400 (Canada)","x-skills-required":["software development","engineering management","AI/ML","traditional models","large language models","backend distributed systems","integrations","decision automation","KYC","AML","risk","compliance systems"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:45:49.061Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Finance","skills":"software development, engineering management, AI/ML, traditional models, large language models, backend distributed systems, integrations, decision automation, KYC, AML, risk, compliance systems","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":225900,"maxValue":298800,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_cda36f17-a29"},"title":"Client Partner","description":"<p>Job Title: Client Partner</p>\n<p>About Hebbia</p>\n<p>Hebbia is an AI platform for investors and bankers that generates alpha and drives upside. Founded in 2020, it powers investment decisions for major asset managers.</p>\n<p>As a Client Partner, you will play a critical role guiding customers through their journey with Hebbia to retain and grow revenue. You will ensure customers realise meaningful value from Hebbia by driving adoption, solving problems, and positioning our platform as essential to their success.</p>\n<p>Responsibilities</p>\n<ul>\n<li>Customer adoption &amp; value realisation: Ensure customers are maximising their use of Hebbia by driving adoption of key features, inspiring engagement, and delivering measurable business impact within their workflows.</li>\n<li>Product expertise: Build deep knowledge of the Hebbia platform; support customers in prompt engineering &amp; template building tailored to their unique workflows; enable them to become confident, independent users and scale AI across their teams.</li>\n<li>Problem solving &amp; triage: Triage customer needs across support resources, solving problems quickly and coordinating cross-functionally to remove blockers.</li>\n<li>Analytical insight: Track account health and usage trends; generate insights and prepare executive-ready materials to demonstrate value and influence expansion conversations with financial sponsors and stakeholders.</li>\n<li>Relationship management: Build strong, trust-based relationships with day-to-day users and senior stakeholders at financial institutions, ensuring Hebbia is positioned as a credible AI partner.</li>\n<li>Commercial savviness: Understand the commercial context of customer contracts, flag risks, and identify opportunities to retain and grow revenue, contributing or even owning renewals.</li>\n<li>AI credibility: Stay curious and informed on AI trends and how large language models (LLMs) can be applied to financial services workflows; understand Hebbia&#39;s technical and functional differentiation and communicate these credibly with clients.</li>\n</ul>\n<p>Requirements</p>\n<ul>\n<li>Meaningful experience in customer-facing enterprise SaaS roles (Customer Success, Account Management, or Consulting), ideally with significant exposure to financial services customers or workflows.</li>\n<li>Strong ownership mindset , you see white space or problems and take initiative to close gaps.</li>\n<li>Distinctive analytical and problem-solving skills , able to interpret data, structure ambiguous questions, and quickly generate actionable solutions in complex customer environments.</li>\n<li>Proficient in prompt engineering, preferably AI-native with low-/no-code tools , and eager to learn how they can transform workflows across Hebbia&#39;s customer industries.</li>\n<li>Excellent relationship builder and communicator , able to inspire adoption and present credibly to both end users and executives in financial institutions.</li>\n<li>Highly responsive, organised, and action-oriented; skilled at managing multiple priorities in a fast-moving environment.</li>\n</ul>\n<p>Bonus</p>\n<ul>\n<li>3+ years of experience managing a portfolio of 10+ key accounts for SaaS products across Financial Services accounts.</li>\n<li>Exhibits strong commercial instincts, consistently exceeding NRR numbers across assigned accounts, proactively expanding account relationships and driving upsell opportunities.</li>\n<li>Has built and/or scaled an AM or CS function at a high-growth SaaS company with complex products and user needs, preferably in Financial Services.</li>\n</ul>\n<p>Compensation</p>\n<p>OTE compensation range for this position is $75,000 and $150,000. The OTE range for those who meet Bonus qualifications is $150,000 and $220,000. OTE is defined as a combination of base salary and performance bonus, and is calculated at a 80/20 split. This position is eligible for a competitive equity grant with significant upside potential.</p>\n<p>Life @ Hebbia</p>\n<ul>\n<li>PTO: Unlimited</li>\n<li>Insurance: Medical + Dental + Vision + 401K + Wellness Benefits</li>\n<li>Eats: Catered lunch daily + doordash dinner credit</li>\n<li>Parental leave policy: 3 months non-birthing parent, 4 months for birthing parent</li>\n<li>Fertility benefits: $15k lifetime benefit</li>\n<li>New hire equity grant: competitive equity package with unmatched upside potential</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_cda36f17-a29","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Hebbia","sameAs":"https://hebbia.com","logo":"https://logos.yubhub.co/hebbia.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/hebbia/jobs/4670226005","x-work-arrangement":"onsite","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["prompt engineering","low-code tools","AI-native","large language models","financial services workflows","customer-facing enterprise SaaS","account management","consulting","relationship building","communication","analytical skills","problem-solving skills"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:38:04.903Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK; New York City"}},"employmentType":"FULL_TIME","occupationalCategory":"Sales","industry":"Finance","skills":"prompt engineering, low-code tools, AI-native, large language models, financial services workflows, customer-facing enterprise SaaS, account management, consulting, relationship building, communication, analytical skills, problem-solving skills"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_faec8dc3-4d3"},"title":"Senior Machine Learning Scientist","description":"<p>We are seeking a Senior Machine Learning Scientist to help grow the Machine Learning Science team. The ideal candidate has a strong knowledge of artificial intelligence (AI), including machine learning (ML) fundamentals and extensive experience with deep learning (DL) methods. They will be responsible for the development of algorithms for early, blood-based detection tests for cancer. They will build on a foundation of ML/DL and statistical skills to develop models for identifying molecular signals from blood. They will also work with computational biologists, molecular biologists and ML engineers to design and drive research experiments, and will have a significant impact on the continued growth of an organisation dedicated to changing the entire landscape of cancer.</p>\n<p>The role reports to the Director, Machine Learning Science. This role can be a Hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Independently pursuing cutting-edge research in AI applied to biological problems</li>\n<li>Building new models or fine-tuning existing models to identify biological changes resulting from disease</li>\n<li>Building models that achieve high accuracy and that generalise robustly to new data</li>\n<li>Applying contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model, ideally suggesting potential biological mechanisms</li>\n<li>Working closely with ML Engineering partners to ensure that Freenome&#39;s computational infrastructure supports optimal model training and iteration</li>\n<li>Taking a mindful, transparent, and humane approach to your work</li>\n</ul>\n<p>Requirements include:</p>\n<ul>\n<li>PhD or equivalent research experience with an AI emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics</li>\n<li>3+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modelling techniques</li>\n<li>Expertise, demonstrated by research publications or industry achievements, in applied machine learning, deep learning and complex data modelling</li>\n<li>Practical and theoretical understanding of fundamental ML models like generalised linear models, kernel machines, decision trees and forests, neural networks</li>\n<li>Practical and theoretical understanding of DL models like large language models or other foundation models</li>\n<li>Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning</li>\n<li>Proficient in current state of the art in ML/DL approaches in different domains, with an ability to envision their applications in biological data</li>\n<li>Proficiency in a general-purpose programming language: Python, R, Java, C, C++, etc.</li>\n<li>Proficiency in one or more ML frameworks such as; Pytorch, Tensorflow and Jax; and ML platforms like Hugging Face</li>\n<li>Experience in ML analysis and developer tools like TensorBoard, MLflow or Weights &amp; Biases</li>\n<li>Excellent ability to communicate across disciplines, work collaboratively, and make progress in smaller steps via experimental iterations</li>\n<li>A passion for innovation and demonstrated initiative in tackling new areas of research</li>\n</ul>\n<p>Nice to have qualifications include:</p>\n<ul>\n<li>Deep domain-specific experience in computational biology, genomics, proteomics or a related field</li>\n<li>Experience in building DL models for genomic data, with knowledge of state-of-the-art DNA foundation models</li>\n<li>Experience in NGS data analysis and bioinformatic pipelines</li>\n<li>Experience with containerized cloud computing environments such as Docker in GCP, Azure, or AWS</li>\n<li>Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment 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_faec8dc3-4d3","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Freenome","sameAs":"https://freenome.com","logo":"https://logos.yubhub.co/freenome.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/freenome/jobs/7963050002","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$173,775 - $246,750","x-skills-required":["PhD or equivalent research experience","Applied machine learning","Deep learning","Complex data modelling","Generalised linear models","Kernel machines","Decision trees and forests","Neural networks","Large language models","Supervised learning","Self-supervised learning","Contrastive learning","Python","R","Java","C","C++","Pytorch","Tensorflow","Jax","Hugging Face","TensorBoard","MLflow","Weights & Biases"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:35:12.037Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Brisbane, California"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Healthcare","skills":"PhD or equivalent research experience, Applied machine learning, Deep learning, Complex data modelling, Generalised linear models, Kernel machines, Decision trees and forests, Neural networks, Large language models, Supervised learning, Self-supervised learning, Contrastive learning, Python, R, Java, C, C++, Pytorch, Tensorflow, Jax, Hugging Face, TensorBoard, MLflow, Weights & Biases","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":173775,"maxValue":246750,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_eb380c70-b51"},"title":"Forward Deployed Engineering Intern (AI Agent)","description":"<p>Join us on this thrilling journey to revolutionize the workforce with AI. The AI Agent team is on a mission to create state-of-the-art AI Agents that solve practical problems for our customers. We are focused on leveraging the latest technologies in Large Language Models (LLMs) and AI Agent systems, while ensuring that the solutions we develop are cost-effective, secure, and reliable.</p>\n<p><strong>About the role:</strong> As a Forward Deployed Engineering Intern on the AI Agent team, you’ll support real-world AI deployments and gain hands-on experience with AI systems in customer environments.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Assist in developing and configuring AI agents using Cresta’s platform tools.</li>\n<li>Help build and test integrations between AI agents and external systems (like APIs or data sources).</li>\n<li>Support performance tuning and troubleshooting of AI agent prototypes.</li>\n<li>Work with customers and internal engineering teams to understand requirements and iterate on solutions.</li>\n<li>Participate in team demos, feedback sessions, and learning opportunities.</li>\n</ul>\n<p><strong>Nice-to-Haves:</strong></p>\n<ul>\n<li>Experience with APIs, web development, or cloud platforms.</li>\n<li>Prior coursework or projects involving AI/ML concepts or LLMs.</li>\n<li>Exposure to prompt engineering or similar experimentation.</li>\n</ul>\n<p>Compensation for this position includes a base salary, equity, and a variety of benefits. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable. We are actively hiring for this role in the US and Canada. Your recruiter can provide further details.</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_eb380c70-b51","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Cresta","sameAs":"https://www.cresta.ai/","logo":"https://logos.yubhub.co/cresta.ai.png"},"x-apply-url":"https://job-boards.greenhouse.io/cresta/jobs/5106468008","x-work-arrangement":"remote","x-experience-level":"entry","x-job-type":"internship","x-salary-range":null,"x-skills-required":["Python","Large Language Models (LLMs)","AI Agent systems","APIs","web development","cloud platforms"],"x-skills-preferred":["prompt engineering","software engineering","artificial intelligence","machine learning"],"datePosted":"2026-04-17T12:28:27.387Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Canada (Remote)"}},"jobLocationType":"TELECOMMUTE","employmentType":"INTERN","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Large Language Models (LLMs), AI Agent systems, APIs, web development, cloud platforms, prompt engineering, software engineering, artificial intelligence, machine learning"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_e5ecff17-84f"},"title":"Senior Forward Deployed Engineer (AI Agent) - UK","description":"<p>Join us on this thrilling journey to revolutionise the workforce with AI.</p>\n<p>The AI Agent team at Cresta is on a mission to create state-of-the-art AI Agents that solve practical problems for our customers. We are focused on leveraging the latest technologies in Large Language Models (LLMs) and AI Agent systems, while ensuring that the solutions we develop are cost-effective, secure, and reliable.</p>\n<p>As an AI Agent Engineer, you&#39;ll be at the forefront of deploying AI agents that address real-world challenges. In this role, you will work closely with customers as well as our software and machine learning engineers, ensuring high-impact AI Agent deployments and contributing to the continuous improvement of our core AI platform. You’ll develop intelligent AI agents, integrate them seamlessly with external systems and offer hands-on technical expertise to ensure successful deployments.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Develop, configure, deploy, and optimise AI agents using Cresta’s AI platform and tools.</li>\n<li>Build AI agent integrations with external systems (APIs, databases, CRMs, etc.) to ensure seamless workflow integration.</li>\n<li>Optimise AI agent performance (e.g. fine-tune prompts and configurations) and troubleshoot issues in complex enterprise environments.</li>\n<li>Collaborate with customers and internal stakeholders to gather technical requirements and translate business needs into AI Agent solutions.</li>\n<li>Conduct interactive demos and present compelling proof-of-concepts to prospective customers, proactively gather feedback, and iteratively refine solutions to meet objectives.</li>\n<li>Define project milestones, create implementation plans, and coordinate execution with internal teams to ensure on-time delivery. Provide a tight feedback loop to our product and engineering teams , identifying gaps, building custom tooling, and influencing the roadmap through real-world deployment learnings.</li>\n<li>Collaborate with PMs to define agent goals, iterate rapidly based on customer feedback, and shape product capabilities that maximise customer ROI.</li>\n<li>Serve as a trusted technical advisor for the customer, guiding best practices for AI agent adoption and usage. 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Our technology is designed to integrate seamlessly into daily working life.</p>\n<p>We are a pioneering company shaping the future of AI.</p>\n<p>Role Summary</p>\n<p>We are seeking a talented and experienced Product Manager to define and execute the product strategy for our GenAI-native coding assistant for developers, one of our most strategic new product lines: Mistral Vibe.</p>\n<p>Built on top of the most performant coding AI models in the market, with more models to come, this product is developed within a leading open source GenAI company that is already deeply trusted by the global developer and engineering community.</p>\n<p>The ambition is clear: make this assistant the preferred tool developers code with and establish it as a market leader in its category.</p>\n<p>As Product Manager, you will contribute to this product end to end, from vision to execution.</p>\n<p>You will define the product strategy, PMF, GTM and growth roadmap and lead the development of a product already backed by a strong pipeline of enterprise customers.</p>\n<p>Working closely with world-class science, engineering and go-to-market teams, you will scale adoption across individual developers and enterprises, grow an existing product motion and consolidate and expand the team around it.</p>\n<p>Your work will directly contribute to building a hundreds of millions revenue stream for Mistral while delivering a tool that significantly increases the productivity and creativity of thousands of developers across the globe.</p>\n<p>What You Will Do</p>\n<p>Define the Future</p>\n<ul>\n<li><p>Set the vision: Shape and evangelize a compelling product strategy for Mistral&#39;s GenAI-native coding assistant, ensuring alignment with company goals and market opportunities.</p>\n</li>\n<li><p>Spot the gaps: Lead market and UX research to uncover unmet needs, competitive whitespaces, and emerging trends enterprise product management.</p>\n</li>\n<li><p>Validate product direction: Engage directly with customers and partners to validate positioning, value propositions and feature priorities.</p>\n</li>\n</ul>\n<p>Build &amp; Ship</p>\n<ul>\n<li><p>Own the lifecycle: Drive end-to-end product development, from ideation to launch and iteration—balancing speed, quality, and user delight.</p>\n</li>\n<li><p>Champion the user: Partner with design and research to craft intuitive, high-impact and developer first experiences, using data and feedback to refine continuously.</p>\n</li>\n</ul>\n<p>Scale &amp; Execute</p>\n<ul>\n<li><p>Go-to-market: Collaborate with marketing and sales to launch products successfully, including pricing, positioning, and adoption strategies.</p>\n</li>\n<li><p>Align stakeholders: Rally science, engineering, design and business teams around priorities, trade-offs and timelines.</p>\n</li>\n<li><p>Prioritize ruthlessly: Maintain a dynamic roadmap that delivers quick wins while advancing long-term bets.</p>\n</li>\n<li><p>Evangelize Mistral Vibe: Act as a product ambassador through customer engagements, thought leadership, writing, and participation in industry and developer events.</p>\n</li>\n</ul>\n<p>Required Qualifications</p>\n<ul>\n<li><p>Product leadership: 10+ years of experience in product management within high-performing product organizations.</p>\n</li>\n<li><p>Business and GTM acumen: Proven experience owning product vision and strategy for enterprise-focused products.</p>\n</li>\n<li><p>Builder mindset: Demonstrated experience operating in ambiguous, fast-growing environments.</p>\n</li>\n<li><p>Developer product expertise: Deep understanding of developer-facing products, developer tools and the day-to-day workflows of software engineers.</p>\n</li>\n<li><p>Generative AI and science collaboration: Solid understanding of how GenAI and large language models are built, trained and deployed.</p>\n</li>\n</ul>\n<p>Preferred Qualifications</p>\n<ul>\n<li><p>Engineering background: Previous experience as a software engineer or strong hands-on engineering background.</p>\n</li>\n<li><p>LLM product experience: Direct experience building or scaling LLM-powered products, with a strong understanding of how generative AI impacts product discovery, roadmapping, evaluation, and iteration cycles.</p>\n</li>\n</ul>\n<p>Additional Information</p>\n<p>Location &amp; 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Join us to be part of a pioneering company shaping the future of AI.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Research and develop novel methods to push the frontier of large language models</li>\n<li>Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech)</li>\n<li>Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale</li>\n<li>Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact</li>\n</ul>\n<p><strong>About You:</strong></p>\n<ul>\n<li>You are a highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java)</li>\n<li>You have hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes)</li>\n<li>You have high engineering competence. 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