Agent Post-Training Research

Responsibilities

• Design and run experiments to improve agentic model behavior across coding, tool use, and multi-agent collaboration
• Own end-to-end improvements to the post-training stack, including RL, data pipelines, and reward signals
• Build evals and environments to expose model failures and translate them into training data or research directions
• Partner with product teams to translate user needs into model improvements
• Improve machinery for large-scale training, including experiment velocity, reliability, and observability
• Debug hard failures in shipped models and develop concrete hypotheses and fixes

Requirements

• Strong technical fundamentals in machine learning, software engineering, systems, or statistics
• Hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, or production ML systems
• Ability to move from vague behavioral problems to concrete experiments and pipelines
• Experience with coding agents, tool-using agents, or synthetic data generation
• Comfortable working across research, product, infrastructure, and safety boundaries

About the Company

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