Research Engineer, Codex

1 day agoSalary: 380K - 500KSan Francisco, USAAiJobs by OpenAI

AI research and deployment company building and deploying frontier AI products, including ChatGPT, Codex, and its API platform.

41 current maintainers27 active leads7 new active leads120 lead step-downs17 early lead departures
San Francisco, United States
About OpenAI

OpenAI’s mission is to ensure artificial general intelligence benefits all of humanity. It consists of the nonprofit OpenAI Foundation and OpenAI Group, a public benefit corporation governed by the Foundation.

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Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will improve the capabilities, reliability, and product fit of agentic models. You might own a research direction, build infrastructure for large training runs, create evals that reveal model failures, or drive a capability from idea through experimentation, integration, and launch. You'll work with researchers, engineers, product, infrastructure, and safety partners to decide what goes into major model runs and ship improvements.

Requirements

  • Strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field
  • Hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, or coding agents
  • Comfort with open-ended problems combining research and engineering
  • Ability to move from a vague problem to a concrete experiment
  • Ability to work across research, product, infrastructure, data, evals, and safety

Responsibilities

  • Design and run experiments that improve agentic model behavior
  • Own end-to-end improvements to the post-training stack including RL, data pipelines, graders, reward signals, and evals
  • Build evals and environments that expose model failures and turn them into training data or fixes
  • Partner with product teams to translate product signal into model improvements
  • Work on early-training and alignment interventions such as data mixtures, objectives, and synthetic data
  • Help decide which integrations and fixes go into major model runs
  • Improve large-scale training machinery: velocity, reliability, observability, reproducibility, cost, latency
  • Take on cross-functional projects touching model training and the production agent harness
  • Debug hard failures in shipped or near-shipped models

Benefits

  • Equity
  • Medical, dental, and vision insurance with employer HSA contributions
  • Pre-tax Health FSA, Dependent Care FSA, and commuter accounts
  • 401(k) with employer match
  • Paid parental leave (up to 24 weeks for birth parents, 20 weeks for non-birthing parents)
  • Paid medical and caregiver leave (up to 8 weeks)
  • Flexible PTO for exempt employees; up to 15 days for non-exempt
  • 13+ paid company holidays and company office closures
  • 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 offices and meal delivery credits
  • Relocation support for eligible employees
  • Charitable donation matching and wellness stipends