# Technical Program Manager, Research Compute Services

**Company**: OpenAI
**Location**: San Francisco, California
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $207K - $285K
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q124605186

**Apply**: https://jobs.ashbyhq.com/openai/e49133e6-4030-4295-b393-1725aa410344?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_26dbc194-0aa

## Description

We are seeking a Technical Program Manager to join the Research Compute Services team at OpenAI. The successful candidate will be responsible for building and owning the tools, data, and platform that turn Research plans and workload signals into concrete compute demand and manage allocations across the fleet.

The Research Compute Services team builds systems that help researchers use OpenAI's compute fleet effectively. The team partners with Research and Compute Infrastructure to support workloads across the compute stack.

As a Technical Program Manager, you will work closely with researchers and engineers 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 deployment, scheduling, and optimization systems.

Key responsibilities:

- Build with Research: Work directly with researchers across pretraining, research inference, and other workloads.

- 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.

- Turn research plans into actionable demand: Develop systems that translate evolving plans and workload requirements into concrete capacity needs.

- Connect capacity supply and demand: Partner with Capacity Planning, Research, and infrastructure teams to reconcile demand with available supply.

- Build reliable data and useful tools: Create data models, views, and automation that show what researchers need, what capacity is available, and how it is being used.

- Connect allocations to workload execution: Partner with engineers working on Kubernetes deployments and scheduling systems.

- Improve allocation and scheduling efficiency: Work with engineers to evaluate optimization approaches.

- Find and address systemic gaps: Use workload and fleet data to identify bottlenecks and recurring manual work.

- Lead technical delivery across teams: Own plans, dependencies, and decisions across Research, Research Compute Services, Capacity Planning, and infrastructure engineering.

- Make progress and tradeoffs clear: Give working teams and leadership a clear view of demand, allocation constraints, delivery progress, and decisions that need attention.

Requirements:

- Strong engineering foundation

- Experience leading complex technical programs

- Practical experience with capacity planning and compute allocations

- Familiarity with Kubernetes deployments and scheduling systems

- Understanding of optimization solvers

- Ability to work closely with researchers and translate their needs into systems

- Resourceful and comfortable with changing priorities

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## Skills

### Required
- Kubernetes
- capacity planning
- compute allocations
- optimization solvers
- Python

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Source: [Apply at jobs.ashbyhq.com](https://jobs.ashbyhq.com/openai/e49133e6-4030-4295-b393-1725aa410344?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)