{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/rl-systems"},"x-facet":{"type":"skill","slug":"rl-systems","display":"Rl Systems","count":4},"x-feed-size-limit":100,"x-feed-sort":"enriched_at desc","x-feed-notice":"This feed contains at most 100 jobs (the most recently enriched). For the full corpus, use the paginated /stats/by-facet endpoint or /search.","x-generator":"yubhub-xml-generator","x-rights":"Free to redistribute with attribution: \"Data by YubHub (https://yubhub.co)\"","x-schema":"Each entry in `jobs` follows https://schema.org/JobPosting. YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f893ff8f-cbc"},"title":"Senior Machine Learning Engineer","description":"<p>Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. As a Senior Machine Learning Engineer, you will join our multidisciplinary effort to deliver new core game mechanics that act in more believable ways by leveraging Machine Learning (ML) and Reinforcement Learning (RL).</p>\n<p>Your responsibilities will include researching, evaluating, and deploying Reinforcement Learning models and techniques for real-time applications, investigating novel imitation learning techniques applicable to the game&#39;s mechanics, and tailoring the functionality of these models and inference frameworks to fit FC&#39;s requirements and target platform constraints.</p>\n<p>You will also develop, optimize, and polish game features that leverage these models to deliver them to FC players, share knowledge on your work by directly engaging with other members of the game team to develop and ship features, evangelize the craft through presentations and interactive demonstrations, promoting Machine Learning best practices and applications within the team, and stay abreast of the latest advancements in the Machine Learning and Reinforcement Learning field.</p>\n<p>Required qualifications include a PhD or Masters degree in Computer Science, Mathematics, or a related field, or equivalent professional experience, strong computer programming fundamentals, proficiency in Python, and experience with C++. You should also have 5+ years of professional experience with ML, RL, and Imitation Learning along with their respective tools and frameworks, and a proven record of building, deploying, and maintaining Machine Learning applications in productized software.</p>\n<p>Preferred qualifications include experience with deploying on-device RL systems, optimizing the RL loop for efficient training with complex environments, optimizing ML models for memory and compute constrained real-time environments, and working with cloud technology and platforms such as containers, Kubernetes, Azure, or AWS.</p>\n<p>Electronic Arts offers a competitive salary range of $141,400 - $204,400 CAD per year, depending on location, and a comprehensive benefits package including vacation, sick time, paid parental leave, extended health and dental coverage, life insurance, disability insurance, and retirement plan.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_f893ff8f-cbc","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Electronic Arts","sameAs":"https://jobs.ea.com","logo":"https://logos.yubhub.co/jobs.ea.com.png"},"x-apply-url":"https://jobs.ea.com/en_US/careers/JobDetail/Senior-Machine-Learning-Engineer/213160","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$141,400 - $204,400 CAD","x-skills-required":["Machine Learning","Reinforcement Learning","Imitation Learning","Python","C++"],"x-skills-preferred":["Deploying on-device RL systems","Optimizing the RL loop for efficient training with complex environments","Optimizing ML models for memory and compute constrained real-time environments","Cloud technology and platforms","Containers","Kubernetes","Azure","AWS"],"datePosted":"2026-04-24T13:14:41.922Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Vancouver"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, Reinforcement Learning, Imitation Learning, Python, C++, Deploying on-device RL systems, Optimizing the RL loop for efficient training with complex environments, Optimizing ML models for memory and compute constrained real-time environments, Cloud technology and platforms, Containers, Kubernetes, Azure, AWS","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":141400,"maxValue":204400,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_02a96eda-a01"},"title":"Researcher, Agentic Post-Training","description":"<p><strong>Compensation</strong></p>\n<p>Estimated Base Salary $295K – $445K</p>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. 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In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p><strong>Team Description</strong></p>\n<p>OpenAI is looking for exceptional researchers to join the Post-Training Frontiers team, which is responsible for post-training the agentic models we ship across Codex, the API, ChatGPT Thinking, and ChatGPT Pro. The Post-Training Frontiers team sets up the pipeline for deciding which integrations can go into the post-training run, develops its own horizontal improvements to the model, and trains the final model.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Own end-to-end research and engineering projects that improve the final post-training of OpenAI’s agentic models.</li>\n</ul>\n<ul>\n<li>Decide, together with partner teams, which integrations are ready for inclusion in major model runs.</li>\n</ul>\n<ul>\n<li>Develop horizontal model improvements across factuality, instruction following, tool/function calling, multi-agent behavior, reasoning-effort calibration, and other broad capabilities.</li>\n</ul>\n<ul>\n<li>Build and improve training, evaluation, grading, and data infrastructure for large-scale RL/post-training runs.</li>\n</ul>\n<ul>\n<li>Create evals and diagnostics that help us understand whether a model is ready to ship.</li>\n</ul>\n<ul>\n<li>Improve the feedback loop from real product usage into post-training, including better ways to learn from implicit user feedback.</li>\n</ul>\n<ul>\n<li>Collaborate closely with Codex, API, ChatGPT, product, training, and other post-training teams to make frontier models more useful, reliable, and agentic.</li>\n</ul>\n<p><strong>Nice to have</strong></p>\n<ul>\n<li>Experience with large-scale model training or RL systems.</li>\n</ul>\n<ul>\n<li>Experience building evals, graders, reward models, or data pipelines for LLM training.</li>\n</ul>\n<ul>\n<li>Experience with coding agents, tool-using agents, browser/computer-use agents, function calling, or multi-agent systems.</li>\n</ul>\n<ul>\n<li>Background in quant, systems, infra, or other environments where you built reliable machinery for high-stakes experimentation.</li>\n</ul>\n<ul>\n<li>Evidence of strong product taste, especially around writing, design, code generation, or agent workflows.</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_02a96eda-a01","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://openai.com/","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/4acc3515-887f-4bc9-8c2a-00f36ae480c3","x-work-arrangement":null,"x-experience-level":null,"x-job-type":"Full time","x-salary-range":"$295K – $445K","x-skills-required":["ML fundamentals","LLMs","RL","RLHF","post-training","evals","model training"],"x-skills-preferred":["large-scale model training","RL systems","graders","reward models","data pipelines","LLM training","coding agents","tool-using agents","browser/computer-use agents","function calling","multi-agent systems","quant","systems","infra","product taste","writing","design","code generation","agent workflows"],"datePosted":"2026-04-24T12:22:09.599Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"ML fundamentals, LLMs, RL, RLHF, post-training, evals, model training, large-scale model training, RL systems, graders, reward models, data pipelines, LLM training, coding agents, tool-using agents, browser/computer-use agents, function calling, multi-agent systems, quant, systems, infra, product taste, writing, design, code generation, agent workflows","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":295000,"maxValue":445000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_5920f836-9df"},"title":"Manager, Machine Learning Research Scientist, GenAI","description":"<p>Scale AI accelerates the development of AI systems by providing data, infrastructure, and tooling that power advanced models. As AI evolves from static models to dynamic, agentic systems, Scale builds foundational research, evaluation methodologies, and agent/RL infrastructure.</p>\n<p>As a Research Scientist Manager, you will lead a world-class team of research scientists and engineers, defining the research roadmap and driving execution from early prototyping to deployment. You&#39;ll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Leading, mentoring, and growing a team of research scientists and engineers working on GenAI research initiatives</li>\n<li>Defining and driving a multi-year research roadmap, identifying key scientific questions, setting milestones, allocating resources, and ensuring rigorous execution</li>\n<li>Collaborating cross-functionally with engineering, product, client-facing teams, and external academic or industry partners to translate research into components, insights, and actionable outcomes</li>\n<li>Communicating compellingly, publishing research, presenting at conferences, engaging in open-source contributions, and representing the team externally</li>\n<li>Driving an inclusive, high-performing culture, helping your team through technical challenges, providing growth opportunities, and attracting top talent</li>\n</ul>\n<p>Ideal candidates will have:</p>\n<ul>\n<li>5+ years of hands-on research experience in machine learning, deep learning, generative models, agent/RL systems, or related domains</li>\n<li>A strong track record of research excellence, including publications in top-tier ML/AI venues</li>\n<li>Experience leading or managing research teams, mentoring, coaching, and developing talent</li>\n<li>Excellent written and verbal communication skills, articulating research ideas and outcomes to technical and non-technical stakeholders</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_5920f836-9df","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/4631811005","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$273,000-$393,000 USD","x-skills-required":["machine learning","deep learning","generative models","agent/RL systems","research leadership","team management","communication","publication","open-source contribution"],"x-skills-preferred":["PhD in machine learning or related domain","experience with large language models","post-training evaluation","agentic/RL environments"],"datePosted":"2026-04-18T16:00:09.239Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; Seattle, WA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, deep learning, generative models, agent/RL systems, research leadership, team management, communication, publication, open-source contribution, PhD in machine learning or related domain, experience with large language models, post-training evaluation, agentic/RL environments","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":273000,"maxValue":393000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_0f6f3674-ac6"},"title":"Director, Enterprise Machine Learning & Research","description":"<p>The Enterprise ML team at Scale works on the front lines of the AI revolution, partnering deeply with customers to identify high-impact business problems and build cutting-edge AI systems using Scale&#39;s proprietary research, data, and infrastructure.</p>\n<p>As Director of Enterprise ML, you will lead a world-class team of research scientists and engineers, define the research roadmap, and drive execution from early prototyping to deployment. 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