Member of Technical Staff - Applied RL
SF$300k - $500kFull-timePosted 3mo ago
About the role
Applied RL-focused MTTS role building end-to-end RL training systems, evaluation, environments and rewards for language-model-based agents, bridging research ideas with production-grade pipelines.
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.
Qualifications
- Strong practical ML engineering ability, demonstrated through shipped systems, open-source projects, competitions, independent projects, or equivalent experience.
- Hands-on experience building, training, evaluating, or debugging ML systems.
- Strong programming ability in Python and experience with at least one major ML framework such as PyTorch or JAX.
- Working understanding of reinforcement learning, supervised learning, optimization, and modern deep learning.
- Ability to independently take an ambiguous technical problem and drive it to a working implementation.
- Ability to collaborate closely with researchers while maintaining high engineering standards.
- Experience building systems that are reliable, maintainable, and usable by other technical team members.
- Clear written and verbal communication.
Skills
Required:PythonML Frameworks (PyTorch or JAX)Reinforcement Learning
Last updated Jul 5, 2026. Interested? Apply on the company site.
About Vmax
Vmax is developing AI capable of open-ended learning. We build systems that exceed human performance across every domain, optimizing beyond the local maxima of learning from human expertise.
Vmax is automating reinforcement learning. We transform proprietary data and evals into new sets of environments. We refine agents on new examples of the tasks they are intended to perform.
AIagentsbessemer-ai-infrastructure-2026environmentsopen-ended learningreinforcement learningreinforcement-learning-platformsresearch
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