Model Designer in United States

About the Team The Product Policy team is responsible for the development, implementation, enforcement, and communication of the policies that govern use of OpenAI’s services, including ChatGPT, GPTs, the GPT Store, Codex, and the OpenAI API. About the Role We are looking for a Research and Advisory Partnerships Lead to build and manage the relationships, partnerships, and advisory structures that bring independent external expertise into our product and policy decisions. 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 will identify and engage researchers, civil society organizations, subject-matter experts, and other external stakeholders whose perspectives can strengthen how we develop and deploy AI. You will establish and manage advisory councils, develop research partnerships with the academic community, and work closely with internal teams to translate external insights into actionable guidance. This role sits at the intersection of product, policy, research, and governance. It is well suited to someone who is comfortable building relationships across disciplines and designing processes that ensure outside expertise meaningfully informs internal decision-making. This role can be based in San Francisco or New York City. 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 will: Develop, launch, and manage external advisory councils and other governance mechanisms that provide structured input on product and product policy. Build and maintain relationships with external experts, researchers, civil society organizations, and other stakeholders who can inform high-priority product and product policy decisions. Identify when external consultation can improve internal decision-making, and develop engagement strategies tailored to specific products, policy questions, and emer

About the Team GTM Growth Engineering builds AI-native products that help OpenAI's go-to-market and B2B marketing organizations scale with greater speed, intelligence, and operational effectiveness. We apply OpenAI models to real business workflows and build the systems that make those applications useful and dependable: customer context, agent behavior, feedback, evaluation, experimentation, and appropriate human oversight. Our work brings together software engineering, applied AI, product, data, and GTM operations. We measure success through the quality of customer engagement, pipeline, conversion, and the effectiveness of our sales and marketing teams. About the Role We're looking for an Applied AI Engineer to build production systems that help AI-powered go-to-market workflows improve over time. You will connect agent behavior, customer and operator feedback, evaluation, experimentation, and business outcomes to make these systems more effective, reliable, and responsive to evolving customer needs. This is a deeply technical, cross-functional role with end-to-end ownership of the agent improvement loop: understand production behavior, identify failure modes, improve how the system decides or acts, and validate the resulting impact. You will partner with Engineering, Product, Data Science, Sales, and B2B Marketing to turn real-world signals into safer, more effective agent behavior and measurable improvements in customer engagement, conversion, qualified pipeline, and team productivity. In this role, you will: Own the production improvement loop across agent behavior, customer and operator feedback, evaluation, experimentation, and verified business outcomes. Instrument agent workflows so model interactions, tool use, decisions, failures, human edits, and downstream outcomes can be understood in context. Define meaningful quality standards, representative evaluation datasets, regression coverage, and production monitoring for real GTM workflows. Investigate why a

About the Team OpenAI is at the center of some of the highest-impact multimodal work in AI. ChatGPT serves a massive global audience, and enables diverse interactions via text, speech, and visuals. As interactive surfaces grow, models also need to adapt to emerging harm, understand user intent and situational context, and respond appropriately. The Chat and Multimodal Safety team is responsible for ensuring that OpenAI’s increasingly multimodal models and products behave safely across these experiences. We develop the research, training methods, and evaluations needed to make these experiences safe. Our work sits at the frontier of responsibly deploying powerful AI, in close partnership with Personal AGI, io, model training, and product teams. About the Role As a Researcher on the Chat and Multimodal Safety team, you will help shape how frontier models perceive and reason the world, and translate that understanding into safe behavior. We’re looking for people who combine deep technical expertise with strong safety judgment. Strong candidates often bridge perception and language: they may have built vision-language models, worked on modality fusion or image encoders, developed multimodal post-training or evaluations, or advanced safety for image, video, or audio systems. 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 will: Define and advance multimodal safety research for text, vision, and audio, connecting perception and semantic understanding to safe model behavior. Build training and evaluation methods for VLMs, including post-training, safety evals, and interventions that help models respond safely and appropriately in varied contexts. Collaborate closely with Personal AGI, Consumer Devices, and product/model teams to translate research into safer ambient, embedded, and personalized multimodal experiences. You might thrive in this role if you:

About the Team The Growth team drives user and revenue growth across ChatGPT’s consumer and business segments as well as other OpenAI products worldwide. We operate across the full funnel - from awareness and acquisition through activation, retention, and expansion - using a combination of global performance marketing, AI-powered workflows, in-product optimization, insights, experimentation, and creative ops engineering. About the Role We are hiring a Lifecycle Lead to build the company-wide owned-channel capability that helps teams reach users with relevant, timely, and trustworthy experiences. This senior, hands-on leader will set the lifecycle strategy, partner with Engineering to build the orchestration and deployment platform, and establish the operating model that allows teams across the company to launch and improve evergreen programs safely at scale. You will sit at the intersection of platform, product, and campaign strategy. You will partner with Engineering, Product, Data Science, and Analytics on the underlying systems, and with Product Marketing Managers and other client teams to design journeys that help new, active, and returning users reach value and build durable habits. In this role, you will: Partner with product to set the company-wide vision, roadmap, and operating model for lifecycle and owned-channel engagement. Partner with Engineering, Product, Data Science, and Analytics to shape the tooling and infrastructure for identity, audiences, eligibility, consent, triggers, orchestration, decisioning, frequency, experimentation, localization, quality assurance, and observability. Define scalable deployment workflows—including self-service and centrally supported paths, intake, templates, approvals, governance, service levels, and incident response—so teams across the company can launch safely and efficiently. Partner with Product Marketing Managers and other client teams to translate audience, product, and business goals into evergreen journey stra

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:

About the Team The CoT Monitorability team at OpenAI studies whether and when the chain-of-thought of frontier reasoning models is monitorable enough to support scalable oversight. We study how to measure monitorability , which training mechanisms affect monitorability, and speculative methods to improve monitorability. While we mostly focus on CoT monitorability at the moment, we care more generally about any form of monitorability, auditing methods, and improving alignment. We were the first to show that chain-of-thought monitoring can be a practical additional safety mechanism, and today our monitoring systems are actively used on OpenAI’s largest RL training runs to detect misbehavior. The issues we surface are then used to help improve our reward functions, environments, etc (without directly training against a CoT monitor). Our work sits in Alignment and intersects with model training, alignment evaluations, monitoring, and frontier-risk research.We care most about monitorability where the stakes are high, and about preserving useful oversight signals as models become more capable. About the Role We’re looking for a researcher with strong empirical ML expertise and a deep interest in model behavior, alignment, or interpretability. Direct chain-of-thought interpretability experience is welcome but not required; strong candidates may come from broader interpretability, alignment, model training, or investigative model-behavior work. As a researcher on the Alignment team, you will design and run experiments that improve our understanding of model monitorability. You will investigate how training interventions across the model-development pipeline influence whether reasoning remains legible, build evaluations that make those questions measurable, and help translate findings into practical oversight and training recommendations. You may also help develop new monitoring models or methods and apply them to OpenAI’s largest training runs. This role is especially well

About the Team OpenAI’s Industrial Compute organization is building the infrastructure required to support the next generation of frontier AI systems. Through a combination of strategic partnerships and self-built data center campuses, we are scaling the power, cooling, electrical, mechanical, and controls infrastructure needed to deliver compute at unprecedented scale. The Commissioning organization is responsible for ensuring this infrastructure is safely tested, validated, integrated, and transitioned into reliable operations. For our self-build campuses, the team operates through a hybrid delivery model: OpenAI provides commissioning leadership, discipline ownership, governance, and project integration, while commissioning partners provide field and test engineering capacity to support inspections, startup, testing, and turnover. About the Role We are seeking a Commissioning Project Lead to own the commissioning strategy and execution for a large-scale, self-build data center project. You will lead the overall commissioning program from early construction planning through startup, functional testing, integrated systems testing, and final turnover. You will establish the commissioning execution plan, integrate commissioning activities into the master project schedule, coordinate multidisciplinary readiness, and lead the vendor commissioning partners providing field and test engineering capacity. This role serves as the primary commissioning interface to project leadership, construction management, contractors, equipment vendors, operations, and commissioning partners. You will be responsible for creating clarity across organizations, identifying readiness and schedule risks early, and ensuring the facility progresses through testing and turnover against clearly defined acceptance criteria. The role will initially support planning and coordination in a hybrid capacity and transition to full-time onsite presence as construction, inspections, startup, testing, and t

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:

About the Team OpenAI’s Education team is building products that advance how people learn with AI. The team works across higher education institutions, K-12 districts, and country-level partnerships, including applied research on how AI affects learning and cognitive outcomes. The team owns owns ChatGPT Edu, ChatGPT for Teachers, and related product/research work. The team partners closely with go-to-market, research, Consumer Learning, and model teams to turn education-specific insights into product experiences that can improve ChatGPT more broadly. Some of our recent work: New Education Plugins for ChatGPT Work and Codex New tools for understanding AI and learning outcomes Education for countries Advancements in higher education Early product work - Introducing Study Mode About the Role We’re looking for a hands-on Tech Lead Manager to lead and manage a team of senior full-stack engineers building AI-native learning experiences in ChatGPT. This person will combine technical execution, product judgment, and people leadership: they will write and ship code, manage engineers, and help shape the product direction for how students and Educators use AI. In This Role, You Will Lead and manage a team of three senior full-stack engineers. Build product experiences for ChatGPT Education, ChatGPT for Teachers, and AI-native learning workflows. Partner with research teams on field studies, randomized control trials, classifiers, data pipelines, and cognitive-outcome measurement. Collaborate with Consumer Learning and model teams to translate education insights into broader ChatGPT behavior and product improvements. Drive execution across product, engineering, research, go-to-market, and partner teams. Help define product strategy, priorities, and delivery plans for a new product pod. You Might Thrive In This Role If You Have several years of direct people-management experience with engineers. Are still highly technical and comfortable doing IC engineering work. Have strong pr

About the Team The Statsig team within OpenAI builds the experimentation, feature rollout, dynamic configuration, and analytics systems that help OpenAI ship products with speed, safety, and evidence. Our work sits on the critical path for how product, engineering, research, and go-to-market teams learn from real-world usage and make high-confidence decisions. Statsig began as an independent company focused on helping builders move faster through trustworthy experimentation and feature management. After joining OpenAI, the team began its next chapter: bringing deep product expertise, customer intuition, and mature platform infrastructure into the product development system used by every OpenAI team. Today, teams across ChatGPT, Codex, model measurement, consumer monetization, business subscriptions, developer products, and shared infrastructure rely on Statsig to safely introduce new capabilities, measure impact, and roll changes forward or back with confidence. We are at a defining moment as adoption accelerates and the platform becomes a company-wide standard. About the Role We are looking for an Engineering Manager, Statsig Product to lead the product engineering organization responsible for Statsig’s post-acquisition journey at OpenAI. You will define how experimentation, rollout, configuration, and analytics become a simple, reliable, and trusted part of how every OpenAI product team ships. You will set strategy across multiple product and platform workstreams, build the organization and leadership structure needed for the next phase, and establish the operating model for a platform that serves teams across the company. The right leader can operate across product strategy, technical architecture, organizational design, developer experience, reliability, and executive alignment. You will help preserve what made Statsig strong while integrating it deeply into how OpenAI launches, measures, learns, and makes product decisions. In this role, you will: Build, lead,

About the Role We're looking for a Head of Competitive Intelligence to build and lead a world-class competitive intelligence function. This person will transform market signals into strategic advantage by developing the frameworks, analysis, and insights that inform our product strategy, go-to-market approach, and executive decision-making. This is not a research role. It's a highly cross-functional strategy role that sits at the intersection of Product, GTM, Research, and Leadership. You'll establish the systems, operating cadence, and analytical rigor that help the company understand where we win, where we're vulnerable, and how the market is evolving. What You'll Do Build and own the company's competitive intelligence strategy and operating model. Develop and maintain comprehensive competitive assessments, including Harvey Ball analyses, feature matrices, product comparisons, pricing analyses, and market landscape reviews. Create executive-ready competitive insights that influence product strategy, roadmap prioritization, pricing, and investment decisions. Build best-in-class objection handling and competitive messaging for Sales, Marketing, Customer Success, and Partnerships. Monitor competitor product launches, model releases, acquisitions, partnerships, pricing changes, funding, and GTM motions, synthesizing complex information into clear strategic recommendations. Establish repeatable processes and tooling for collecting, validating, and distributing competitive intelligence across the company. Partner closely with Product Management to inform roadmap decisions and identify areas of strategic differentiation. Collaborate with Marketing to sharpen positioning and messaging based on competitive dynamics. Support executive leadership with board-ready competitive analyses and market briefings. Build dashboards and reporting that track competitive movements and emerging industry trends. Develop frameworks that evaluate competitors across capabilities, enterprise r

About the Team OpenAI is building AI systems that can help professionals perform complex, high-value work with greater speed, rigor, and creativity. Investment banking is one of the most demanding environments for knowledge work: bankers must synthesize fragmented information, exercise judgment under pressure, and produce precise, defensible models, analyses, and client materials. Our team works across Research, Product, Engineering, and Go-to-Market to make OpenAI's models genuinely useful for these workflows. We translate real professional work into product requirements, evaluations, training signals, and repeatable customer solutions. We care not only whether a model can generate an answer, but whether it can deliver accurate, defensible work that experienced bankers can trust and use. 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. About the Role We are looking for a Subject Matter Expert in Investment Banking to help define what excellent AI-assisted banking work looks like and turn that standard into better models and products. You will bring deep, current knowledge of how investment banking work is actually performed, including company and industry research, financial analysis and modeling, valuation, diligence, transaction execution, and the creation and review of client materials. You will use that expertise to design realistic tasks and evaluations, create and assess high-quality reference work, diagnose model failures, and help our technical teams improve model behavior and product experiences. This is a hands-on individual-contributor role for someone who enjoys both doing the work and explaining what makes it good. You should be comfortable moving between an Excel model, a presentation, a source document, an evaluation rubric, a product prototype, and a conversation with researchers or customers. You will help us distinguish outputs that merely look pl

About the Role As Enterprise Sales Manager, Banking, you will build and lead a team of Account Directors focused on driving strategic growth across the world’s largest banking institutions. You’ll be a hands-on front-line leader responsible for helping your team navigate complex enterprise sales cycles, deepen executive relationships, and drive adoption of OpenAI’s platform across highly regulated banking environments. This role will shape how OpenAI partners with global banks as they rethink productivity, operations, customer engagement, risk management, and software development through AI. You will help define the GTM strategy, operating model, and industry playbook for one of OpenAI’s most strategic verticals. Key Responsibilities Recruit, develop, and lead a high-performing team of Account Directors focused on large enterprise banking institutions across North America. Create a strong coaching culture with frequent deal reviews, account strategy sessions, ride-alongs, and structured 1:1s that elevate team performance. Define and refine the GTM strategy for banking, including account prioritization, executive engagement strategy, and territory planning. Drive disciplined pipeline generation, forecasting accuracy, and operational rigor across a complex enterprise sales motion. Guide teams through highly consultative, multi-stakeholder opportunities involving technology, security, compliance, legal, and procurement stakeholders. Help customers translate AI and API capabilities into measurable business outcomes across banking use cases such as employee productivity, customer operations, risk and compliance, software engineering, knowledge management, and workflow automation. Lead teams selling into highly regulated environments with a deep understanding of banking-specific risk, governance, and data security considerations. Partner closely with Product, Solutions Architecture, Technical Success, Legal, Security, and Finance to help customers successfully deploy AI a

About the Team The Safety Systems team is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Model Safety Research team aims to fundamentally advance our capabilities for precisely implementing robust, safe behavior in AI models, and to leverage these advances to make OpenAI’s deployed models safe and beneficial. This requires a breadth of new ML research to address the growing set of safety challenges as AI becomes more powerful and used in more settings. Key focus areas include how to enforce nuanced safety policies without trading off helpfulness and capabilities, how to make the model robust to adversaries, how to address privacy and security risks, and how to make the model trustworthy in safety-critical domains. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. About the Role OpenAI is seeking a senior researcher with passion for AI safety and experience in safety research. Your role will set directions for research to enable and empower safe AGI and work on research projects to make our AI systems safer, more aligned and more robust to adversarial or malicious use cases. You will play a critical role in shaping how a safe AI system should look like in the future at OpenAI, making a significant impact on our mission to build and deploy safe AGI. In this role, you will: Conduct state-of-the-art research on AI safety topics such as RLHF, adversarial training, robustness, and more. Implement new methods in OpenAI’s core model training and launch safety improvements in OpenAI’s products. Set the research directions and strategies to make our AI systems safer, more aligned and more robust. Coordinate and collaborate with cross-functional team

About the Team The Post-Training Frontiers team is responsible for training the frontier agents OpenAI ships to the world (GPT-Next). We train the flagship agentic models behind Codex, ChatGPT, and the API through large-scale reinforcement learning. The team’s work spans four areas. First, execution and science: working with teams across OpenAI to decide what can go into the final model and how, using scientific experiments and evals that are representative of the final pipeline so issues can be recognized early. Second, RL scaling: executing the final large-scale reinforcement learning run, making sure GPUs are used efficiently and training stays healthy. Third, research: improving horizontal capabilities like instruction following, factuality, memory, and multi-agent behavior, where the team’s broad visibility helps identify cross-cutting improvements across teams and domains. Fourth, engineering: maintaining the infrastructure stack and internal tools to ensure that both the final run and all integrations go as smoothly as possible and that the systems are easy to work with. About the Role This role focuses on keeping our frontier RL training runs fast, reliable, and unblocked. You will work across engineering and infrastructure problems as they emerge, from scaling and orchestration issues to inference bottlenecks, numerical problems, and hardware failures, as well as supporting large horizontal integrations in the big run, like multi-agent capabilities or memory. This is a role for a strong generalist who quickly learns anything needed for the task, has high attention to detail, debugs deeply, and is motivated by fixing the highest-impact problem in front of the team. In this role, you will: Keep large-scale async RL training runs moving by jumping into the most urgent engineering and infrastructure problems. Debug issues across training systems, inference, orchestration, scaling, and distributed infrastructure. Improve the reliability and efficiency of RL trai