Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI
Codex
Experimentation
LLM
Machine Learning @ 3
Performance Optimization @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
The Codex team builds AI systems that write code, reason about software, and act as intelligent agents for developers and non-developers. The team works across research, engineering, product, and infrastructure, owning the lifecycle of experimentation, deployment, and iteration on coding capabilities.
As a Performance & Systems Engineer, you will be responsible for whole-system optimization across a complex stack spanning LLM inference, cloud orchestration, agentic work management, and multiple product surfaces. You will identify and implement high-leverage changes across infrastructure, modeling, and product layers to make Codex agents faster and cheaper to serve.
This is a high-ownership role focused on identifying performance bottlenecks and directly improving the experience of millions of users. The role is based in San Francisco, California, and follows a hybrid work model requiring three days in the office per week.
Responsibilities
- Identify and address inefficiencies across the Codex system stack, including agent behavior, LLM inference, container orchestration, and related systems.
- Build tooling to measure, profile, and optimize system performance at scale.
- Collaborate with researchers and engineers to implement high-return changes that improve latency and cost.
Requirements
- Experience operating across both machine learning systems and cloud infrastructure.
- Ability to work through ambiguous and complex problems and identify effective solutions.
- A holistic approach to performance optimization, balancing speed, cost, and user experience.
Benefits
- Base salary of $295,000–$445,000 per year.
- Equity, performance-related bonuses for eligible employees, and comprehensive benefits.
- Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
- Pre-tax Flexible Spending Accounts and commuter benefits.
- 401(k) retirement plan with employer match.
- Paid parental, medical, caregiver, sick, and safe leave.
- Paid time off and company holidays.
- Mental health and wellness support.
- Employer-paid basic life and disability coverage.
- Annual learning and development stipend.
- Daily office meals and eligible meal delivery credits.
- Relocation support for eligible employees.
- Additional benefits may include charitable donation matching and wellness stipends.
OpenAI is an equal opportunity employer and is committed to providing reasonable accommodations to applicants with disabilities. Background checks will be administered in accordance with applicable law.