OpenAI Technical Program Manager at OpenAI owning CPU capacity planning and management across Research and Compute infrastructure. Responsible for integrated planning of CPU, storage, and network capacity to support AI workloads at scale.
Responsibilities
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.
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 and connectivity plans, ordering inputs, and delivery milestones. Coordinate CPU and network allocations as capacity is deployed across the fleet.
Understand workload architecture and performance requirements well enough to challenge assumptions and influence technical decisions. Help teams evaluate resource sizing, regional placement, data movement, storage choices, and acceptable alternatives when supply is constrained.
Drive fleet efficiency programs that reclaim unused capacity, rightsize workloads, modernize infrastructure, and improve placement or resource sharing. Measure the capacity released and cost improvements while preserving workload performance and reliability.
Scale integrated capacity planning across CPU, storage, and network in partnership with resource owners. Improve demand intake, forecasts, scenario models, inventory and allocation records, and the tools that automate recurring workflows.
Partner with cloud providers, Finance, Procurement, and engineering to shape capacity orders, commitments, and renewal decisions. Evaluate regional availability, delivery lead times, cost, and technical fit, and drive resolution of supply gaps.
Align capacity plans with cluster and application deployment milestones. Work across infrastructure owners to ensure CPU, storage, and network dependencies are ready when workloads need them, and resolve gaps that would delay usable capacity.
Give teams and leadership a clear view of demand, supply, allocation tradeoffs, forecast changes, and risks. Turn ambiguous or competing needs into decisions, accountable owners, and executable plans.
