Software Engineer, RL Training Infra

OpenAI

Software Engineer enhancing RL training infrastructure for AI models. Collaborating with research and infrastructure teams to improve training efficiency and reliability in fast-paced environments.

Posted 5/23/2026full-timeSan Francisco • California • 🇺🇸 United StatesMid-LevelSenior💰 $295,000 - $445,000 per yearWebsite

Tech Stack

Tools & technologies

Distributed Systems

About the role

Key responsibilities & impact

Keep large-scale RL training runs moving by jumping into the most urgent engineering and infrastructure problems.
Debug issues across training systems, inference, orchestration, scaling, and distributed infrastructure.
Solve hard technical problems at the boundary between research and engineering: scaling experiments, improving training reliability, debugging distributed systems, reducing latency and cost, and making new capabilities robust under real workloads.
Improve reliability and efficiency for RL training runs.
Help researchers who are developing infra-heavy integrations, such as multi-agent capabilities or memory.
Turn recurring operational issues into better tools, systems, processes, or abstractions.
Work closely with research, infrastructure, and partner teams during tight model run timelines.
Become useful quickly in messy, ambiguous areas where ownership matters more than a perfectly scoped project.
Debug failures that cut across model behavior, training data, RL systems, evaluation infrastructure, serving systems, and agent harnesses, then turn those failures into hypotheses, fixes, and durable improvements.

Requirements

What you’ll need

Want to train and ship our frontier models and ensure we make agents genuinely useful for developers, enterprises, researchers, and everyday users.
Strong generalist engineer with experience in some layer of ML infrastructure.
Worked on RL, inference, scaling, training systems, orchestration, or adjacent ML infrastructure.
Learn extremely quickly and are comfortable operating across unfamiliar layers.
Strong debugger with high ownership, low ego, and excellent communication.
Land in a messy area with tight timelines, become useful quickly, and gradually raise the quality of the whole system.
Energized by fast-moving environments where reliability, speed, and judgment matter.
Like building load-bearing systems and processes when that is what the team needs, even if the work is not glamorous.

Benefits

Comp & perks

Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
401(k) retirement plan with employer match
Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
Mental health and wellness support
Employer-paid basic life and disability coverage
Annual learning and development stipend to fuel your professional growth
Daily meals in our offices, and meal delivery credits as eligible
Relocation support for eligible employees
Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

reinforcement learningdebuggingscalinginferencetraining systemsorchestrationdistributed systemslatency reductioncost reductionmulti-agent capabilities

Soft Skills

strong generalist engineerexcellent communicationhigh ownershiplow egoquick learneradaptabilityproblem-solvingcollaborationjudgmentability to work under tight timelines