{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/agentic-reasoning"},"x-facet":{"type":"skill","slug":"agentic-reasoning","display":"Agentic Reasoning","count":3},"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_5aa5b947-f4d"},"title":"Staff Machine Learning Research Scientist/ Engineer, Agents","description":"<p>About Scale AI</p>\n<p>At Scale AI, our mission is to accelerate the development of AI applications. This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents.</p>\n<p>Responsibilities</p>\n<ul>\n<li>Explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation.</li>\n<li>Contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable 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 venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.).</li>\n<li>At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.</li>\n</ul>\n<p>Nice to Have</p>\n<ul>\n<li>Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax.</li>\n<li>Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.</li>\n<li>Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.</li>\n<li>Familiarity with agentic reasoning methods such as STaR and PLANSEARCH</li>\n<li>Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.</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>$259,200-$324,000 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_5aa5b947-f4d","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/4488520005","x-work-arrangement":"hybrid","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$259,200-$324,000 USD","x-skills-required":["Pytorch","Jax","Tensorflow","LLMs","Agent frameworks","Agentic reasoning methods","Cloud technology stack"],"x-skills-preferred":["Open source LLM fine-tuning","Bespoke LLM fine-tuning projects"],"datePosted":"2026-04-18T15:59:17.656Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; Seattle, WA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Pytorch, Jax, Tensorflow, LLMs, Agent frameworks, Agentic reasoning methods, Cloud technology stack, Open source LLM fine-tuning, Bespoke LLM fine-tuning projects","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":259200,"maxValue":324000,"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_eddc20bf-1ad"},"title":"Research Engineer, Codex","description":"<p><strong>Research Engineer, Codex</strong></p>\n<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Department</strong></p>\n<p>Research</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$380K – $445K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong><strong>About the Team</strong></strong></p>\n<p>The Codex team is responsible for building state-of-the-art AI systems that can write code, reason about software, and act as intelligent agents for developers and non-developers alike. Our mission is to push the frontier of code generation and agentic reasoning, and deploy these capabilities in real-world products such as ChatGPT and the API, as well as in next-generation tools specifically designed for agentic coding. We operate across research, engineering, product, and infrastructure—owning the full lifecycle of experimentation, deployment, and iteration on novel coding capabilities.</p>\n<p><strong><strong>About the Role</strong></strong></p>\n<p>As a member of the Codex team, you will advance the capabilities, performance, and reliability of AI coding models through a combination of research, experimentation, and system optimization. You’ll collaborate with world-class researchers and engineers to develop and deploy systems that help millions of users write better code, faster—while also ensuring these systems are efficient, cost-effective, and production-ready.</p>\n<p>We’re looking for people who combine deep curiosity, strong technical fundamentals, and a bias toward impact. Whether your strengths lie in ML research, systems engineering, or performance optimization, you’ll play a pivotal role in pushing the state of the art and bringing these advances into the hands of real users.</p>\n<p>This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.</p>\n<p><strong><strong>In this role, you might:</strong></strong></p>\n<ul>\n<li>Design and run experiments to improve code generation, reasoning, and agentic behavior in Codex models.</li>\n</ul>\n<ul>\n<li>Develop research insights into model training, alignment, and evaluation.</li>\n</ul>\n<ul>\n<li>Hunt down and address inefficiencies across the Codex system stack—from agent behavior to LLM inference to container orchestration—and land high-leverage performance improvements.</li>\n</ul>\n<ul>\n<li>Build tooling to measure, profile, and optimize system performance at scale.</li>\n</ul>\n<ul>\n<li>Work across the stack to prototype new capabilities, debug complex issues, and ship improvements to production.</li>\n</ul>\n<p><strong><strong>You might thrive in this role if you:</strong></strong></p>\n<ul>\n<li>Are excited to explore and push the boundaries of large language models, especially in the domain of software reasoning and code generation.</li>\n</ul>\n<ul>\n<li>Have strong software engineering skills and enjoy quickly turning ideas into working prototypes.</li>\n</ul>\n<ul>\n<li>Think holistically about performance, balancing speed, cost, and user experience.</li>\n</ul>\n<ul>\n<li>Bring creativity and rigor to open-ended research problems and thrive in highly iterative, ambiguous environments.</li>\n</ul>\n<ul>\n<li>Have experience operating across both ML systems and cloud infrastructure.</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_eddc20bf-1ad","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/793964ae-d40b-45e3-9798-84f4b6da48c5","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$380K – $445K • Offers Equity","x-skills-required":["ML research","systems engineering","performance optimization","software engineering","cloud infrastructure"],"x-skills-preferred":["large language models","software reasoning","code generation","agentic reasoning"],"datePosted":"2026-03-06T18:41:00.782Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"ML research, systems engineering, performance optimization, software engineering, cloud infrastructure, large language models, software reasoning, code generation, agentic reasoning","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":380000,"maxValue":445000,"unitText":"YEAR"}}}]}