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Agent Post-Training, Computer Use Research

OpenAI· Research
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San Francisco$295k - $445k + bonusFull-timePosted 3mo ago

About the role

Role focused on teaching models to operate computers, including desktop and browser navigation, tool usage, complex workflows, and long-horizon tasks. Works with research, product, infrastructure, and safety teams to drive post-training improvements for agentic computer-use capabilities in OpenAI’s frontier models.

Responsibilities

  • Design and run experiments that improve agentic model behavior for complex computer use, including desktop and browser.
  • Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis.
  • Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions.
  • Partner with Codex and ChatGPT product teams to understand what users need and translate product signal into model improvements.
  • Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior.
  • Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs.
  • Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness.
  • Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments.
  • Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes.

Qualifications

  • Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before.
  • Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems.
  • Are excited by open-ended problems where the path is unclear, the signal is noisy, and the right answer requires both research taste and engineering execution.
  • Care about product impact and model behavior, not just benchmark movement. You have opinions about what makes an agent useful, reliable, honest, tasteful, and easy to work with.
  • Can move from a vague behavioral problem to a concrete experiment: define the hypothesis, build the pipeline, run the model, analyze the result, and decide what to do next.
  • Are comfortable working across research, product, infrastructure, data, evals, and safety boundaries, and can communicate clearly with each group.
  • Like building load-bearing systems and processes when that is what the team needs, even if the work is not glamorous.
  • Want to train and ship the models that make agents genuinely useful for developers, enterprises, researchers, and everyday users.

Skills

Required:Machine learning fundamentalsLLMs and reinforcement learningExperiment design and analysisCross-functional collaboration

Benefits

  • 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
  • Mental health and wellness support
  • Employer-paid basic life and disability coverage
  • Annual learning and development stipend
  • 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
Last updated Sep 3, 2026. Interested? Apply on the company site.

About OpenAI

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