Product Manager, Core Models
OpenAI is hiring a Product Manager, Core Models in San Francisco, United States. It pays $347k-$490k a year and Level rates it ; you can apply on OpenAI.
Level's read on this job
- Works on AI ●●●○ is how Level rates this AI product manager role: the daily work is on AI products, without building the model.
- Pay on this posting starts 93% higher than the typical AI product manager posting on Level.
- Some of the work can be done remotely, according to the posting.
- The posting mentions Claude, AI evaluation and AI research among its tools and skills.
- OpenAI has 793 other open roles on Level.
AI in this role
Lead product management for core AI models, shaping capabilities, evaluation systems, and deployment loops from research to production.
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.
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.
How we rate this
Product Manager, Core Models at OpenAI rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in AI product manager jobs at this level
Pay
- This job starts at
- $347k
- Typical AI product manager job
- $180k
This posting starts 93% above the typical AI product manager job. See AI product manager jobs
Questions you could be asked
- How do you decide that one model's output is better than another's for a given task?
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where product management was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where data science was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Evaluation, AI Research, Product Management, Machine learning, and Data Science. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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