Technical Program Manager (AI Research Compute)

Location: San Francisco, United States; hybrid

Salary: $207K–$285K annually, plus equity.

Company

OpenAI is an AI research and deployment company developing and safely deploying general-purpose artificial intelligence.

What you will do

• Build with researchers across pretraining, research inference, synthetic data generation, sampling, and reinforcement learning, translating workload needs into improvements to compute services, tooling, and scheduling.
• Own the roadmap and delivery of demand-capture, allocation, and research compute management tools, data, and platforms from requirements and design through adoption and ongoing improvement.
• Translate evolving research plans into concrete capacity requirements, including resources, timing, and constraints, and reconcile demand with available compute supply.
• Create data models, views, automation, and self-service workflows showing demand, available capacity, allocations, and utilization.
• Connect allocation plans with Kubernetes deployments and scheduling systems, including evaluation of fleet-wide and local optimization solvers, constraints, objectives, and tradeoffs.
• Lead technical delivery across Research, Research Compute Services, Capacity Planning, and infrastructure engineering while clarifying dependencies, decisions, progress, and adoption.

Requirements

• Strong engineering foundation developed through relevant education or demonstrated technical experience.
• Experience leading and delivering complex technical programs involving large-scale compute, distributed systems, infrastructure platforms, or research environments.
• Practical experience with capacity planning, supply and demand management, compute allocations, and the tools and data supporting those decisions.
• Experience personally building or materially contributing to tools, data systems, or automation used by engineering or research teams; comfort working directly with code and operational data.
• Familiarity with Kubernetes deployments and scheduling systems, including how resource constraints and placement decisions affect workload execution.
• Understanding of optimization solvers for fleet-wide allocation and local scheduling, including the ability to evaluate constraints, objectives, and tradeoffs.
• Ability to work with researchers to understand evolving requirements and translate them into practical, useful systems.
• Ability to own ambiguous technical problems, establish a path forward, drive delivery and adoption, and communicate technical decisions and priorities across engineering, Research, and leadership.
• Resourcefulness, comfort with changing priorities, and thoughtful interest in the impacts of AGI.

Culture & Benefits

• Engineer-first TPM team working closely with Research Compute Services, Research, Capacity Planning, and infrastructure engineering.
• Hands-on technical work involving code, data, prototyping, workflow automation, and tools used by teams every day.
• Full-time hybrid work in San Francisco.
• Equity is offered in addition to salary.
• OpenAI is an equal opportunity employer and provides reasonable accommodations for applicants with disabilities.
• Background checks are administered under applicable law for US-based candidates.