Member of Technical Staff - Applied RL

Vmax is an applied research lab developing AI systems capable of open-ended learning. The Member of Technical Staff will build and improve reinforcement learning training systems, translate research ideas into implementations, design evaluations, and improve the reliability and speed of experimentation.

Responsibilities:

• Build and improve RL training pipelines for language model based agents
• Translate research ideas into working implementations, including reward functions, verifiers, environment interfaces, rollout pipelines, and evaluation harnesses
• Design experiments that test whether RL methods are actually improving model behavior, sample efficiency, robustness, or generalization
• Create quality monitoring tools for  RL experiments, including regression tests, eval suites, and reward-hacking checks
• Debug unstable training runs, diagnose poor learning dynamics, and identify whether failures come from algorithms, rewards, data, infrastructure, or evals
• Build 0→1 systems for new RL workflows, then harden them into reusable infrastructure
• Improve the reliability, reproducibility, and speed of experimentation across RL projects
• Own technically ambiguous projects end to end, from problem framing through implementation, evaluation, and iteration