Technical Program Manager, Research Compute Services at OpenAI · LumiJobs

Responsibilities

This is a hands-on technical role. You will build alongside researchers and engineers, working directly with code and data to prototype solutions, automate workflows, and deliver tools that teams use every day. You will combine technical judgment and program leadership to connect capacity planning with the deployment, scheduling, and optimization systems that make allocated compute usable.
Build with Research. Work directly with researchers across pretraining, research inference, and other workloads. Treat these communities as core users, and translate their needs into improvements across compute services, tooling, and scheduling.
Own Research demand and allocation systems. Own the roadmap and delivery of the tools, data, and platform used to capture demand, support allocation decisions, and manage allocations. Carry this work from requirements and design through adoption and ongoing improvement.
Turn research plans into actionable demand. Develop systems that translate evolving plans and workload requirements into concrete capacity needs, including resource requirements, timing, and constraints.
Connect capacity supply and demand. Partner with Capacity Planning, Research, and infrastructure teams to reconcile demand with available supply. Build the tools and workflows needed to evaluate scenarios, manage changes, and make allocation tradeoffs visible to decision makers.
Build reliable data and useful tools. Create data models, views, and automation that show what researchers need, what capacity is available, what has been allocated, and how it is being used. Improve self-service workflows for requesting and managing compute.
Connect allocations to workload execution. Partner with engineers working on Kubernetes deployments and scheduling systems so allocation plans reflect workload constraints and translate into resources that researchers can use.
Improve allocation and scheduling efficiency. Work with engineers to evaluate optimization approaches, including solvers operating at fleet and local scheduling levels. Help define constraints and objectives, assess tradeoffs, and measure improvements in fleet utilization.
Find and address systemic gaps. Use workload and fleet data to identify bottlenecks, unused capacity, and recurring manual work. Build durable improvements to the tools and systems behind those problems.
Lead technical delivery across teams. Own plans, dependencies, and decisions across Research, Research Compute Services, Capacity Planning, and infrastructure engineering. Keep teams aligned on what needs to be built, how it will be adopted, and who will operate it.
Make progress and tradeoffs clear. Give working teams and leadership a clear view of demand, allocation constraints, delivery progress, and decisions that need attention.
You might thrive in this role if you:

Technical Program Manager, Research Compute Services

Responsibilities

Company

OpenAI

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