Vmax
Member of Technical Staff - RL Algorithms
San Francisco · Staff+
Sponsorship not specified$300k-$500kDetected 62 days ago
PythonAlgorithmsMachine LearningPyTorchData EngineeringLLMsRoboticsResearchCommunication
About the role
- RL has become the de-facto method of post-training LLMs.
- We are limited by the sample efficiency of the current policy gradient algorithms in use today, and are looking for a talented researcher to weave together pre-LLM and post-LLM approaches to learning from experience.
Responsibilities
- Develop new RL algorithms for post-training language models.
- Collaborate with researchers working on environments, evals, interpretability, reward modeling, and infrastructure to turn algorithmic ideas into reliable training systems.
- Own and develop a research agenda within Vmax, from identifying promising directions to executing experiments and communicating results.
- Experience designing and running rigorous ML experiments, including ablations, baselines, evaluation design, and failure analysis.
Requirements
- Track record of research excellence, as demonstrated by publications, open source work, deployed AI systems, or other substantial technical contributions.
- Experience with large-scale ML infrastructure, distributed training, experiment tracking, data pipelines, and debugging unstable training runs.
- Expertise with Python and at least one major ML framework such as PyTorch or JAX.
- Ability to work independently on open-ended research problems and turn ambiguous ideas into concrete experimental programs.
Nice to have
- Experience with LLM pre-training.
- Strong understanding of reward modeling, verifiers, process supervision, outcome supervision, or automated evaluation systems.
- Demonstrated software engineering ability
- Strong communication skills, especially the ability to explain algorithmic ideas, empirical results, and research implications to both technical and non-technical audiences
- This role is based in our San Francisco office
Compensation
- The expected salary range for this position is $300,000 - $500,000 USD
Benefits
- Adapt ideas from pre-LLM reinforcement learning, such as model-based RL, temporal abstraction, and value-based learning, to modern LLM and agentic settings.
- PhD or equivalent experience in machine learning, reinforcement learning, or a closely related field.
- Deep understanding of modern machine learning, especially reinforcement learning, representation learning, and large language models.
Company info
- V max is an applied research lab developing AI capable of open-ended learning.
- We are building systems to exceed humans in all capacities by optimising beyond the local maxima of learning from human expertise.
This listing is sourced directly from Vmax's careers page and normalized into a canonical job model.