Job description

About the Team The Core Models team helps shape how OpenAI’s frontier models are built, measured, and launched. We work across Research, Engineering, Model Design, Data Science, and Product to turn advances in model capabilities into reliable, useful experiences for people. Our scope includes model planning and launches as well as building data flywheels, evaluations and measurement systems to ensure our models have strong capabilities and behavior. About the Role As a Product Manager for the Core Models team, you'll be at the forefront of defining and guiding the future of how our AI models work in real-world applications. You will connect user needs to model and systems decisions: how prompts are understood; how information is aggregated and made useful for training and evaluation data; and how capabilities move from research prototypes into the mainline model and launch stack. You will operate comfortably across research, infrastructure, and consumer product surfaces, creating clarity where ownership and technical boundaries are still emerging. 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: - Translate user and product goals into clear model requirements, system architecture choices, and research priorities across query understanding, indexing, retrieval, ranking, tool boundaries, data, training, inference, and evaluation. - Build closed learning loops that turn product usage, explicit feedback, and other user signals into datasets, evaluations, experiments, training priorities, and launch decisions. - Define success across offline evaluations and online product metrics, balancing model quality, usefulness, latency, safety, reliability, and cost. - Partner closely with post-training research, applied product engineering, Model Design, and Data Science to integrate capabilities into the mainline model stack. - Create reusable platforms and operating systems for evaluation, experimentation, and signal collection so that new capabilities improve faster over time. - Use concrete product failures and emerging user needs to identify gaps, form hypotheses, and shape the next wave of research and product investment. You might thrive in this role if you: - Have deep expertise in product management or closely related experience, including ownership of technically complex products or platforms. - Bring deep fluency in one or more relevant domains: search and information retrieval, recommendation or personalization systems, ML platforms, large-scale data systems, model evaluation, or AI product infrastructure. - Know how to pair offline evaluation with online experimentation and user signals, and can distinguish a useful metric from a convenient one. - Earn the trust of researchers and engineers through technical depth, crisp judgment, and a willingness to engage directly with the details. - Combine consumer product taste with systems rigor, and care about both the quality people feel and the infrastructure that makes it repeatable. - Move quickly in ambiguous environments, communicate directly, and help teams make sound decisions without waiting for perfect information. - Care deeply about how increasingly capable models affect people, and bring humility, judgment, and a strong sense of responsibility to the work. 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 cdn.openai.com. 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 form.asana.com. 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 form.asana.com. OpenAI Global Applicant Privacy Policy cdn.openai.com 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.

Requirements

Must-haves

About the Team
Build closed learning loops that turn product usage, explicit feedback, and other user signals into datasets, evaluations, experiments, training priorities, and launch decisions.
Define success across offline evaluations and online product metrics, balancing model quality, usefulness, latency, safety, reliability, and cost.
Partner closely with post-training research, applied product engineering, Model Design, and Data Science to integrate capabilities into the mainline model stack.
Create reusable platforms and operating systems for evaluation, experimentation, and signal collection so that new capabilities improve faster over time.
Use concrete product failures and emerging user needs to identify gaps, form hypotheses, and shape the next wave of research and product investment.
You might thrive in this role if you:
Have deep expertise in product management or closely related experience, including ownership of technically complex products or platforms.
Bring deep fluency in one or more relevant domains: search and information retrieval, recommendation or personalization systems, ML platforms, large-scale data systems, model evaluation, or AI product infrastructure.
Know how to pair offline evaluation with online experimentation and user signals, and can distinguish a useful metric from a convenient one.
Earn the trust of researchers and engineers through technical depth, crisp judgment, and a willingness to engage directly with the details.
Combine consumer product taste with systems rigor, and care about both the quality people feel and the infrastructure that makes it repeatable.
Move quickly in ambiguous environments, communicate directly, and help teams make sound decisions without waiting for perfect information.
Care deeply about how increasingly capable models affect people, and bring humility, judgment, and a strong sense of responsibility to the work.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiml

Platform: ashby
Effort: quick