5 months ago
Base Salary
$295k - $380k/yr
Responsibilities
- Review, improve, and clean up code across training frameworks and adjacent infrastructure.
- Identify risky or low-quality changes before they land and raise the code quality bar.
- Debug issues across ML training systems, GPUs, clusters, networking, and related infrastructure.
- Unblock researchers and engineers dealing with broken training jobs, flaky workflows, and brittle internal tooling.
- Improve the reliability, maintainability, and usability of the robotics team’s training framework.
- Solve practical engineering problems that directly affect team velocity.
Requirements
- Strong software engineering fundamentals and excellent code review judgment.
- Experience with ML systems, training frameworks, GPUs, distributed systems, infrastructure, or similarly complex technical environments.
- Ability to read and debug unfamiliar codebases quickly and identify root causes.
- Ability to ship high-quality code with strong velocity and pragmatic judgment.
- A low-ego, responsive approach focused on helping researchers and engineers move faster.
- Preference for highly effective hands-on individual-contributor work over broad, process-heavy initiatives.
- Experience reviewing messy, fast-moving, or AI-generated codebases.
Benefits
- Based in San Francisco, California, with an expectation to work in the office five days per week.
- Relocation assistance is offered to new employees.
Categories
About OpenAI
OpenAI builds and deploys large-scale AI models and tools—including ChatGPT, GPT-4–class models, DALL·E, and Whisper—sold via APIs and enterprise subscriptions to developers and businesses. It monetizes through usage-based API pricing and ChatGPT Plus/Team/Enterprise, and also reaches customers via Microsoft’s Azure OpenAI Service. Founded in 2015 and headquartered in San Francisco, it operates as a private partnership.