Agent Post-Training Research

The role

You will improve the capabilities, reliability, and product fit of OpenAI's agentic models. This involves designing experiments, owning post-training stack improvements, and building evals to drive model capabilities into products.

What you will do

• Design and run experiments that improve agentic model behavior.
• Own end-to-end improvements to the post-training stack.
• Build evals and environments that expose model failures.
• Partner with Codex, API/platform, and ChatGPT product teams.
• Work on early-training and alignment interventions.
• Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs.
• Improve the machinery for large-scale training and launch.
• Take on cross-functional projects touching model training and product infrastructure.
• Debug hard failures in shipped or near-shipped models.

Required qualifications

• 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, coding agents, tool-using agents, or production ML systems.

About the company

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.