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Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role Notion is looking for a Recruiting Program Manager to help design, build, and scale the systems and programs that power how we hire. This is a role for someone who moves fast, takes ownership, and doesn't wait to be told what to do — someone who operates with both strategic altitude and operational precision, and knows how to bring clarity and momentum to complex cross-functional work. We're at an inflection point in how we think about recruiting at Notion, and this role sits at the center of it. You'll partner closely with Recruiters, Recruiting Operations, People Operations, and senior leadership to drive some of our highest-priority initiatives — building the programs and processes that define how Notion finds, evaluates, and brings in exceptional talent. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve The scope of this role will evolve with the team's highest priorities. Some examples of what you might work on: Interviewer systems and efficacy — design the systems, structures, and standards that make Notion's interviewing reliably great: how we train interviewers, how we measure their effectiveness, how we calibrate quality over time, and how we continuously raise the bar; this includes programs like Interviewer 101, Hiring Manager Training, and functional interviewer certifications tailored to specific teams Interviewer pool health — own the systems and strategy behind how we maintain a healthy, well-mapped interviewer pool, manage AI and experimental interview formats, and keep quality high at scale Recruiting team onboarding and enablement — build and run programs that get new recruiters up to speed quickly and keep the team operating at a high level Specialty hiring programs — provide program management support for specialized hiring motions like internal mobility, M&A integration, and other high-priority strategic initiatives Cross-functional playbooks and infrastructure — build the processes, communications, and coordination frameworks that help Recruiting run with more consistency, clarity, and scale Skills You'll Need to Bring 5+ years of relevant experience in program management, recruiting operations, or a highly cross-functional role in a fast-moving environment High agency — you move fast, take ownership end-to-end, and don't wait for perfect information or explicit direction to get started. Ambiguity doesn't scare you. Builder mentality — you're most energized when creating something new or improving something that doesn't yet work well Strong AI skills — think beyond generative AI. We're looking for folks with hands-on experience building custom agents, skills, etc and have taught them to others. You're genuinely excited about using AI to change how a core business function works Strong project management skills — you can lead complex initiatives from scoping through execution, managing stakeholders, timelines, and competing priorities along the way; you're equally comfortable driving short-term sprints and stewarding long-range programs that evolve over months or years Proven ability to operate with discretion and high judgment on sensitive or high-profile work Strong analytical instincts — you use data to evaluate program health, spot patterns, and make informed decisions Outstanding written and verbal communication — you tailor your message to the audience and create clarity across all levels of the organization Nice to Haves Experience with recruiting program management workstreams through different stages of recruiting evolution You use Notion and love it — you get what we're building Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. For roles based in San Francisco or New York City, the estimated base salary range for this role is $140,000 - $195,000 per year. By clicking “Submit Application”, I understand and agree that Notion and its affiliates and subsidiaries will collect and process my information in accordance with Notion’s Global Recruiting Privacy Policy and NYLL 144 . #LI-Onsite A Note on AI You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on. Equal Opportunity & Accommodations We hire talented people from a wide range of backgrounds. If you’re excited about this role but don’t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know. Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.
About the Team The Legal team is building the next generation of AI-powered products and experiences for the legal industry. We are exploring how advanced AI systems can transform legal workflows, improve access to information, and enable legal professionals and organizations to work more effectively. As a founding member of the Legal engineering team, you will help define the technical foundation for this new product area from the earliest stages. You’ll operate at the intersection of AI, product, and real-world legal workflows—identifying opportunities, building prototypes, and turning emerging ideas into scalable products that can create meaningful impact. We operate with a startup-like mindset inside OpenAI: small teams, rapid iteration cycles, and a willingness to explore bold ideas, learn quickly, and adapt based on user feedback. Our goal is to build products that meaningfully improve how legal professionals work while leveraging OpenAI’s cutting-edge models and infrastructure. About the Role As a Founding Full-Stack Software Engineer on the Legal team, you will help imagine, build, and scale new AI-powered products for the legal industry. You’ll work across the stack to design intuitive user experiences, build robust backend systems, and create the foundations for products used by legal professionals and organizations around the world. You’ll have significant ownership from the earliest stages—working closely with product, design, research, and go-to-market partners to understand customer needs, shape product direction, and deliver high-impact solutions. This includes rapidly prototyping new concepts, building production-quality applications on top of OpenAI’s platforms, and developing new technical approaches when existing systems are not sufficient. We’re looking for engineers who thrive in ambiguity, have strong product instincts, and enjoy building from 0→1. You should be comfortable moving quickly, making thoughtful technical decisions, and taking ownership across the entire product lifecycle—from initial exploration through launch and scale. In this role, you will: Build and ship full-stack products that leverage OpenAI models to solve complex problems in legal workflows. Own projects end-to-end, from early prototypes and technical exploration through production deployment and iteration. Design and develop intuitive user experiences across frontend and backend systems. Build scalable, reliable systems on top of OpenAI’s internal platforms and APIs while contributing new technical foundations where needed. Partner closely with product managers, designers, researchers, applied AI teams, and customers to identify opportunities and translate insights into impactful products. Rapidly prototype and experiment with new AI capabilities, using real-world feedback to guide product decisions. Develop a deep understanding of legal workflows, customer needs, and industry challenges to inform technical strategy. Help establish engineering culture, technical standards, and product practices as an early member of the team. Learn from and contribute alongside deeply experienced engineers while fostering a high-trust, inclusive, and candid team environment. You might thrive in this role if you: Have 6+ years of professional software engineering experience. Have built and shipped full-stack applications end-to-end, from early prototypes through production systems. Are excited by ambiguous, open-ended problems and can turn broad ideas into shipped products. Have strong frontend and backend engineering skills and enjoy working across the stack. Are comfortable moving quickly, iterating based on feedback, and making pragmatic technical decisions. Have strong product instincts and enjoy collaborating directly with users and cross-functional partners. Are energized by emerging AI capabilities and the opportunity to rethink how software is built. Learn quickly, pick up new technologies as needed, and choose the right tools to solve problems effectively. Thrive in small, high-ownership teams where engineers have significant influence over product direction and technical strategy. Welcome direct, constructive feedback and offer the same to others with clarity and respect. About OpenAI 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. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
About the Team The Core Models team shapes how our models interact with people. We view the model as the product itself, aiming for intuitive experiences that exceed user expectations and feel like magic. About the Role As a Model Designer, you’ll have an outsized impact on how our models interact and resonate with users. You’ll strike a delicate balance between maximizing the model’s capabilities, reading in between the lines in user queries to understand how best to help, and upholding user trust. We’re looking for people who are passionate about the intersection of design, technology, and user experience — and are up for the challenge of defining new human-AI interaction paradigms. 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. In this role, you’ll join a small team in evolving and expanding the model design function. You will: Collaborate closely with researchers to understand, predict, and design model behavior. Partner with product managers and designers across the company to ensure a cohesive voice and approach. Proactively identify ways to improve our models based on product sense, user feedback, quantitative insights, and the research roadmap. Come up with creative strategies for collecting high-quality data. Do whatever needs to be done to make our models better. You might thrive in this role if you: Possess exceptional taste, creativity, and writing skills, allowing you to craft responses that delight users. Don’t mind ambiguity — you’re happy to throw yourself into a new, unfamiliar environment, build relationships, define a problem, and make progress. Love experimentation, and are willing to test and reject new ideas when the results don’t pan out. Exhibit high levels of empathy and self-awareness required to serve everyone in the world. Enjoy tackling profound and often philosophical questions while always driving towards clarity. Demonstrate technical intuition to learn how changes in data can affect overall model behavior. About OpenAI 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. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
About the Team At OpenAI, our User Safety & Risk Operations (USRO) team helps protect our products and users from abuse, fraud, safety risks, and other forms of misuse. We operate at the front line of real-world safety and risk management, translating user and operational signals into timely decisions, effective interventions, and improvements to our systems. This role sits on a team focused on building operational capacity for new, ambiguous, and fast-moving areas of work. The team defines what needs to be built, creates the operating model to support it, and works with partner teams to make the work scalable and durable over time. About the Role We are seeking a Device Safety & Risk Operations Specialist to build the safety operating model for a new category of consumer hardware. This is a senior individual-contributor role for someone who can turn emerging product risks and incomplete requirements into practical workflows, controls, launch plans, and durable systems. You will define how product-safety incidents, critical escalations, regulated cases, and privacy-sensitive issues should be identified, investigated, escalated, resolved, and learned from. You will also establish operational requirements for case management, data access, decision logging, quality assurance, monitoring, and cross-functional response. You will stand up priority workflows through launch and early operations, then help transition them into durable homes across USRO and partner teams. The right person combines deep operational judgment with strong technical and hardware product fluency. They can move from executive-level risk framing to detailed workflow design, tabletop exercises, launch readiness, frontline guidance, and post-launch improvement. Location / work model: San Francisco, CA; hybrid, 3 days/week in-office. Please note: This role may involve exposure to sensitive or concerning material. Strong discretion, judgment, and resilience are essential. In This Role, You Will: Build the end-to-end safety and risk operating model for new consumer hardware, from early requirements through launch and early-life operations. Define incident taxonomies, severity levels, decision rights, escalation criteria, response pathways, and closure standards. Develop operational playbooks for product-safety incidents, critical escalations, safety advisories, corrective actions, and other high-risk events. Design workflows for regulated and privacy-sensitive cases, including restricted handling, evidence requirements, auditability, and partner escalation. Translate safety and operational needs into requirements for tooling, case management, data access, monitoring, logging, and automation. Establish clear ownership boundaries across Product, Engineering, Legal, Privacy, Product Policy, Support, Product Quality, and other operational partners. Build launch-readiness plans, tabletop exercises, training, quality controls, reporting, and post-launch monitoring. Use operational data, customer signals, product telemetry, and case outcomes to identify patterns and improve upstream products and systems. Determine where AI and automation can improve triage, evidence assembly, consistency, and response while preserving appropriate human judgment. Stand up priority workflows, operate them through launch and early-life stabilization, and transition them into durable homes across USRO and partner teams. You Might Thrive in This Role If You: Have 8+ years of relevant experience in device safety, product safety, consumer hardware operations, technical program management, or a related field. Have built a complex safety or risk program from an ambiguous starting point through launch and scaled operation. Understand the realities of handling high-severity incidents, regulated workflows, sensitive customer information, and time-critical escalations. Can translate product, engineering, legal, privacy, and policy constraints into workflows that operational teams can execute. Are technically fluent and can reason through data flows, telemetry, access controls, audit logs, case systems, automation, and failure modes. Use data to assess workflow health, identify emerging patterns, evaluate quality, and make risk-based decisions. Can establish clear accountability across teams with overlapping responsibilities and different risk tolerances. Know how to balance launch speed with safety controls, monitoring, rollback criteria, and longer-term system development. Communicate clearly with operational, technical, legal, and executive audiences when evidence is incomplete or tradeoffs are difficult. Are highly practical and willing to build the workflow, not only define the strategy. Experience supporting consumer hardware, connected devices, or other products used in shared environments. Experience with product-safety investigations, recalls, field failures, safety advisories, or hazardous-product handling. Experience designing workflows involving privacy-sensitive sensor, diagnostic, media, or household data. Familiarity with warranty, repair, reverse logistics, identity recovery, fraud, or ownership disputes. Experience building vendor training, quality-assurance, incident-response, or specialist-review programs. About OpenAI 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. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
About the Team Our economics team is continuously working to improve our understanding of an AI-driven economy. About the Role We are seeking a highly technical Economist to join the OpenAI Economic Research team studying the real-world economic impacts of AI. This role is designed for economists with up to 5 years of professional experience post-Ph.D. who are interested in using novel, large-scale datasets to study how AI is reshaping economic systems. We are looking for candidates with deep expertise in at least one core domain relevant to AI’s economic impact, and an interest in contributing to a broader research agenda spanning labor markets, firm behavior, market dynamics, and macroeconomic change. This is an individual contributor role where the candidate will organize and execute on their own data-oriented projects. You will work at the intersection of economic research, data science, and public policy to produce rigorous empirical work that informs decision-makers across the public, industry, and government. Research Areas of Interest We are particularly interested in candidates with demonstrated expertise in one or more of the following areas: Economic Measurement of AI Impact (e.g., adoption trajectories, labor market transitions, productivity growth, and forecasting/scenario modeling for AI-driven economic change) Macroeconomic Implications of AI (e.g., productivity, technology diffusion, economic growth) AI and the Labor Market (e.g., employment, wages, job search, task-level impacts, skill acquisition) Applicants are not expected to have experience across all domains. We aim to build a team with complementary strengths across these areas. In this role, you will: Design and execute empirical research using large-scale observational or experimental data. Apply causal inference and/or structural modeling techniques to study AI-driven economic change. Collaborate with cross-functional teams to translate research questions into testable frameworks and applicable takeaways across policy, product, and our organization. Produce policy-relevant outputs, including academic papers, technical reports, and briefings. Contribute to the development of new measurement approaches for AI’s economic impact. Use AI across your responsibilities to scale your research impact. You might thrive in this role if you have: A PhD in Economics or a related quantitative field. 3–5 years of relevant work experience (industry or policy research). Strong background in econometrics and applied microeconomics Demonstrated experience working with large or complex datasets, with demonstrated proficiency in SQL. Proficiency in statistical programming (e.g., Python, R). Research related to labor economics, industrial organization, macroeconomics, or technological change. Experience working with platform, labor market, or firm-level data. Familiarity with causal inference, machine learning methods, or structural modeling. About OpenAI 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. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Artifacts, you will train frontier models to create polished, useful work products: documents, spreadsheets, slide decks, dashboards, reports, analyses, and other interactive or editable artifacts. You will help teach our models to move from a vague user goal to a finished artifact with strong structure, visual taste, domain judgment, correctness, and low latency. This work will require owning improvements across our post-training stack, including RL, data pipelines, graders, reward signals, evals, and behavioral analysis. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you will: Design and run experiments that improve agentic model behavior for complex software and plugins.. Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions. Partner with Codex and ChatGPT product teams to understand what users need and translate product signal into model improvements. Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior. Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs. Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness. Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments. Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes. You might thrive in this role if you: Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before. Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems. Are excited by open-ended problems where the path is unclear, the signal is noisy, and the right answer requires both research taste and engineering execution. Care about product impact and model behavior, not just benchmark movement. You have opinions about what makes an agent useful, reliable, honest, tasteful, and easy to work with. Can move from a vague behavioral problem to a concrete experiment: define the hypothesis, build the pipeline, run the model, analyze the result, and decide what to do next. Are comfortable working across research, product, infrastructure, data, evals, and safety boundaries, and can communicate clearly with each group. Like building load-bearing systems and processes when that is what the team needs, even if the work is not glamorous. Want to train and ship the models that make agents genuinely useful for developers, enterprises, researchers, and everyday users. Have some prior background in consulting, finance, marketing, operations, or data science. About OpenAI 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. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Computer Use, you will teach models to operate computers. You will help train models that can navigate browsers and desktops, use tools and applications, reason through complex workflows, collaborate with users and other agents, and complete long-horizon tasks with reliability and judgment. This work sits at the intersection of frontier model training, product behavior, evaluation, and systems engineering, and will directly shape the computer-use capabilities shipped in OpenAI’s next generation of agents. Currently, our models are the best in the world at this behavior! You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Design and run experiments that improve agentic model behavior for complex computer use , including desktop and browser. Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions. Partner with Codex and ChatGPT product teams to understand what users need and translate product signal into model improvements. Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior. Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs. Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness. Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments. Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes. You might thrive in this role if you Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before. Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems. Are excited by open-ended problems where the path is unclear, the signal is noisy, and the right answer requires both research taste and engineering execution. Care about product impact and model behavior, not just benchmark movement. You have opinions about what makes an agent useful, reliable, honest, tasteful, and easy to work with. Can move from a vague behavioral problem to a concrete experiment: define the hypothesis, build the pipeline, run the model, analyze the result, and decide what to do next. Are comfortable working across research, product, infrastructure, data, evals, and safety boundaries, and can communicate clearly with each group. Like building load-bearing systems and processes when that is what the team needs, even if the work is not glamorous. Want to train and ship the models that make agents genuinely useful for developers, enterprises, researchers, and everyday users. 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