How to Run RL Autoresearch with Agent Skills | Nemotron Labs

Coding agents can now run RL experiments on open models like Nemotron end to end — handling setup, running multi-hour autoresearch campaigns, and dramatically improving model accuracy on tasks you define. NVIDIA verified agent skills make this practical on a single GPU: structured workflow instructions that keep an agent on-task, preserve memory across long runs, and drive the full experiment loop. This tutorial livestream shows you how, using NeMo RL and NeMo Gym. What you'll learn: How to set up NeMo RL on a GPU instance using a coding agent How to build a NeMo Gym environment and run a goal-driven autoresearch campaign How to use NVIDIA verified agent skills to maintain session state and structure the RL experiment loop How to implement an off-policy RL algorithm from a research paper with agent-led paper-to-code Automating RL research? Specializing open models like Nemotron for your own domain? Bring your questions — the team will answer them live.