OpenAI

AI Research and Deployment

SeniorSoftwareEngineer,MLSystems&TrainingInfrastructure

$295–380k San Francisco, California, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Software Engineer, ML Systems & Training Infrastructure at OpenAI. Skills: ML Systems, Training Infrastructure, Code Review. Review code. Improve code”

What You'll Achieve.

Keep training framework healthy; Keep surrounding infrastructure healthy; Unblock researchers and engineers; Improve people's lives

Industry & Context.

AI Research and Deployment
Problems you'll solve

Get to root cause

Eligibility Requirements

Expected in office 5 days per week, Relocation assistance

What They're Looking For.

Must Have

Software engineering fundamentals, Excellent code review judgment, Experience with ML systems, Experience with training frameworks, Experience with GPUs, Experience with distributed systems, Experience with infrastructure, Read and debug unfamiliar codebases quickly, Ship high-quality code with velocity, Pragmatic judgment, Responsive

Nice to Have

Experience reviewing messy codebases, Experience reviewing fast-moving codebases, Experience reviewing AI-generated codebases

What You'll Do.

Identify risky changes

Raise code quality bar

Improve maintainability

Move quickly on practical problems

How You'll Work.

Team & Collaboration

Work with product team

Full Job Description

About the Team The OpenAI Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role As a Senior Software Engineer, ML Systems & Training Infrastructure, you will be a deeply hands-on engineering force multiplier for the robotics team. You will help keep the training framework and surrounding infrastructure healthy, review and improve code quickly, debug failures across ML systems and infrastructure, and unblock researchers and engineers when the path from idea to working training job gets rough. We’re looking for people who love writing, reading, reviewing, and fixing code; who can get productive quickly in unfamiliar systems; and who bring strong practical judgment without a lot of ego or process overhead. This role will be based in San Francisco, CA and be expected in office 5 days per week and offer relocation assistance to new employees. In this role, you will: - 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 without slowing the team down. - Debug issues across ML training systems, GPUs, clusters, networking, and related infrastructure. - Help researchers and engineers unblock broken training jobs, flaky workflows, and brittle internal tooling. - Improve the reliability, maintainability, and usability of the robotics team’s training framework. - Move quickly on practical engineering problems that directly affect team velocity. You might thrive in this role if you: - Have strong software engineering fundamentals and excellent code review judgment. - Have experience with ML systems,

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