Product Manager, Core Models (AI)

TL;DR

Product Manager, Core Models (AI): Define and guide how AI core models work in real-world applications by translating user and product goals into model requirements, system architecture choices, and research priorities. Focus on building closed learning loops, integrating capabilities into the mainline model stack, and balancing offline evaluations with online product metrics across quality, usefulness, latency, safety, reliability, and cost.

Location: San Francisco, CA (hybrid: 3 days in the office per week). Relocation assistance available.

Salary: $347K–$490K + Offers Equity

Company

OpenAI is an AI research and deployment company building frontier models and safely deploying them through products.

What you will do

• 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 convert product usage and explicit user feedback into datasets, evaluations, experiments, training priorities, and launch decisions.
• Define success using both offline evaluations and online product metrics, balancing model quality, usefulness, latency, safety, reliability, and cost.
• Partner 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 to improve new capabilities faster over time.
• Use product failures and emerging user needs to identify gaps, form hypotheses, and shape the next wave of research and product investment.

Requirements

• Deep expertise in product management (or closely related experience) with ownership of technically complex products or platforms.
• Fluency in one or more relevant domains: search and information retrieval, recommendation/personalization, ML platforms, large-scale data systems, model evaluation, or AI product infrastructure.
• Ability to pair offline evaluation with online experimentation and user signals, and to distinguish useful metrics from convenient ones.
• Technical depth and judgment to earn trust from researchers and engineers and engage directly with details.
• Comfort operating in ambiguous environments and communicating directly to drive sound decisions.

Culture & Benefits

• Hybrid work model: 3 days in the office per week.
• Relocation assistance for new employees.
• Compensation includes $347K–$490K plus offers equity.
• Work focused on safely deploying increasingly capable AI models with responsibility and humility.