Researcher, Agentic Post-Training

Details

OpenAI's Post-Training Frontiers team is responsible for post-training the agentic models shipped across Codex, the API, ChatGPT Thinking, and ChatGPT Pro. The team sets up the pipeline for deciding which integrations can go into the post-training run, develops horizontal improvements to the model, and trains the final model. The role focuses on delivering high-impact horizontal improvements (factuality, instruction following, function calling, multi-agent collaboration, calibrated reasoning effort, tool use, or improving model taste) and on making large post-training runs faster, more reliable, and easier for researchers to use.

Responsibilities

• Own end-to-end research and engineering projects that improve the final post-training of OpenAI’s agentic models.
• Decide, together with partner teams, which integrations are ready for inclusion in major model runs.
• Develop horizontal model improvements across factuality, instruction following, tool/function calling, multi-agent behavior, reasoning-effort calibration, and other broad capabilities.
• Build and improve training, evaluation, grading, and data infrastructure for large-scale RL/post-training runs.
• Create evals and diagnostics that help determine whether a model is ready to ship.
• Improve the feedback loop from real product usage into post-training, including better ways to learn from implicit user feedback.
• Collaborate closely with Codex, API, ChatGPT, product, training, and other post-training teams to make frontier models more useful, reliable, and agentic.

Requirements

• Strong ML fundamentals and hands-on experience with LLMs, RL, RLHF, post-training, evals, or model training.
• Highly capable engineering skills: able to move quickly in complex systems and make pragmatic technical decisions.
• Ability to own ambiguous problems end-to-end without needing a tightly specified roadmap.
• Goal-oriented mindset and willingness to do unglamorous but load-bearing work when it matters.
• Excellent product taste in model behavior and ability to reason about what “good” looks like across many user-facing domains.
• Comfortable working across research, infrastructure, data, evals, and product boundaries.
• Excitement to train and ship frontier agentic models that power Codex, ChatGPT, and the API.

Nice to have

• Experience with large-scale model training or RL systems.
• Experience building evals, graders, reward models, or data pipelines for LLM training.
• Experience with coding agents, tool-using agents, browser/computer-use agents, function calling, or multi-agent systems.
• Background in quant, systems, infra, or other environments where you built reliable machinery for high-stakes experimentation.
• Evidence of strong product taste, especially around writing, design, code generation, or agent workflows.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. The company emphasizes safety and human needs in AI development and is an equal opportunity employer. Background checks will be administered in accordance with applicable law. OpenAI is committed to providing reasonable accommodations to applicants with disabilities.

Compensation & Benefits

• Estimated base salary range: $295K – $445K (base pay may vary depending on market location, knowledge, skills, and experience).
• Total compensation may include equity and performance-related bonuses for eligible employees.
• Benefits include medical, dental, and vision insurance; Health Savings Account contributions; flexible and paid time off; 401(k) with employer match; 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; and additional taxable fringe benefits such as charitable donation matching and wellness stipends.
• Relocation support for eligible employees.