Agent Post-Training Research

Responsibilities

• Design and run experiments to improve agentic model behavior, including coding, tool use, function calling, and multi-agent collaboration.
• Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, and evals.
• Build environments and evaluations that expose model failures and translate those findings into training data or research directions.
• Partner with product teams (Codex, API, ChatGPT) to translate user needs into model improvements.
• Improve large-scale training machinery, focusing on experiment velocity, reliability, observability, and production readiness.
• Debug complex 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 Large Language Models (LLMs).
• Experience with Reinforcement Learning (RL) or RLHF/RLAIF.
• Experience with post-training techniques, evaluations, or synthetic data generation.
• Ability to move from vague behavioral problems to concrete, executable experiments.

Preferred Qualifications

• Experience building production-grade ML systems or coding agents.
• Experience with long-horizon task execution and calibrated reasoning.
• Ability to work cross-functionally across research, product, and safety boundaries.

Benefits

• Competitive base salary and generous equity.
• Comprehensive medical, dental, and vision insurance.
• 401(k) retirement plan with employer match.
• Paid parental leave and flexible PTO.
• Daily meals in the office and mental health support.
• Annual learning and development stipend.

About the Company

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of AI capabilities and seek to safely deploy them to the world through our frontier products.