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Technical Program Manager, Global Infrastructure Planning

OpenAI

Technical Program Manager, Global Infrastructure Planning is a still-open role at OpenAI on Jobrow. Location: Hybrid · San Francisco · California · United States. Listed pay: $207k–$285k. Sourced from the company's public Ashby board. First seen 5 hours ago; last confirmed 5 hours ago. Apply on the employer ATS — Jobrow is not the employer.

Pay
$207k–$285k
Workplace
Hybrid
Location
San Francisco · California · United States
First seen
5 hours ago
Last seen
5 hours ago
Board
Ashby
Apply

About this role

ABOUT THE TEAM The Compute Infrastructure team runs the GPU fleet and large compute clusters that support OpenAI’s research, ChatGPT, and the API.

  • Function: Infrastructure
  • Seniority: manager
  • aws
  • gcp
  • azure

Location & pay

Hybrid · San Francisco · California · United States Listed pay on Jobrow: $207k–$285k.

Source

Jobrow reads the public Ashby board for OpenAI. First seen 5 hours ago; last seen 5 hours ago. We are not the employer — apply only on the company ATS.

Posting

ABOUT THE TEAM The Compute Infrastructure team runs the GPU fleet and large compute clusters that support OpenAI’s research, ChatGPT, and the API. Our work spans GPUs, CPUs, storage, networking, and cloud infrastructure, bringing these systems together so teams can train and serve models at scale. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. ABOUT THE ROLE You will own CPU capacity planning and management across Research and Compute. Working with infrastructure owners, you will lead integrated planning for CPU, storage, and network capacity across OpenAI’s global fleet. You will connect workload demand and GPU deployment plans with the foundational resources required to support pretraining, research, and application infrastructure at scale. You will work closely with workload owners, infrastructure engineering, network deployment teams, Finance, and cloud providers to turn forecasts into supply and allocation plans. You will understand workload architecture, guide decisions when capacity is constrained, and drive opportunities to improve utilization and reduce waste. Your work will span planning over multiple years and ongoing capacity management across regions and providers, including AWS, GCP, Azure, and OCI. 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: - Lead CPU demand planning across Research, Compute, and application infrastructure, including foundational services, data acquisition, container platforms, robotics, and services supporting GPU clusters. Maintain forecasts that capture workload growth, regional and hardware requirements, timing, and acceptable alternatives. - Translate workload growth and GPU fleet plans into integrated CPU, storage, and network requirements. Partner with engineering to determine the capacity, throughput, bandwidth, connectivity, and placement needed to support pretraining and applications at scale. - Reconcile current and incoming supply with demand, model constrained scenarios, and drive allocation and prioritization decisions. Lead CPU allocation planning and fulfillment, including quota transfers, rebalancing, and reclaims. - Partner with network engineering and deployment teams to translate regional demand into bandwidth

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