Performance & Systems Engineer, Codex

OpenAI OpenAI · AI Frontier · San Francisco, CA · Research

The role focuses on optimizing the performance and cost of AI systems, specifically the Codex agents, which involve LLM inference, cloud orchestration, and agentic work management. The engineer will hunt down inefficiencies, build tooling for measurement and profiling, and collaborate to improve latency and cost.

What you'd actually do

  1. Hunt down and address inefficiencies across the Codex system stack, from agent behavior to LLM inference to container orchestration, and beyond.
  2. Build tooling to measure, profile, and optimize system performance at scale.
  3. Collaborate with researchers and engineers to land high-ROI changes that improve latency and cost.

Skills

Required

  • operating across both ML systems and cloud infrastructure
  • diving into messy, ambiguous problems
  • thinking holistically about performance

Nice to have

  • experience operating across both ML systems and cloud infrastructure
  • enjoy diving into messy, ambiguous problems and emerging with clear wins
  • think holistically about performance, balancing speed, cost, and user experience

What the JD emphasized

  • whole-system optimization
  • complex, evolving stack
  • significantly faster and cheaper to serve
  • generalists who thrive in ambiguity
  • high-ownership role
  • messy, ambiguous problems
  • emerging with clear wins
  • holistically about performance

Other signals

  • LLM inference
  • agentic work management
  • system optimization
  • performance bottlenecks