Researcher, Artifacts - Agent Post-Training
Core
Train frontier models to create polished, useful work products (documents, spreadsheets, slide decks, dashboards, reports) with strong structure, visual taste, and low latency.
Role type
Senior Researcher, Agent Post-Training
Builds
Data, environments, graders, training methods, and feedback loops for OpenAI's next-generation agents.
Domain
AI / Machine Learning / Agent Systems
Deliverable
production ML models
Required skills
Machine learning fundamentals, LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, production ML systems
Preferred skills
Software engineering, systems, statistics, consulting, finance, marketing, operations, data science
Technologies
RL, data pipelines, reward signals, evals, synthetic data, multi-agent systems
Responsibilities
Design and run experiments to improve agentic model behavior for complex software and plugins; Own end-to-end improvements to the post-training stack; Build evals and environments to expose model failures; Partner with product teams to translate user needs into model improvements; Work on early-training and alignment interventions; Decide which capabilities are ready for major model runs; Improve large-scale training machinery; Debug hard failures in shipped models.
Seniority
Senior, hands-on IC