Vmax
Research Fellowship - Open Endedness
San Francisco · Staff+
Sponsorship not specifiedDetected 62 days ago
PythonMachine LearningPyTorchLLMsA/B TestingDesign SystemsResearchCommunication
About the role
- This 3 to 6 month fellowship is for PhD students or equivalent early-career researchers who want to work on LLMs that can learn in open-ended settings.
Responsibilities
- Develop RL methods for agents that can discover useful objectives, tasks and curricula without relying entirely on human-specified rewards.
- Build training loops where agents learn from interaction, exploration, novelty, competence progress, self-generated challenges, or other nonstandard reward signals.
- Own and develop a research agenda within Vmax, from identifying promising directions to executing experiments and communicating results.
- Familiarity with unsupervised/automated environment design, asymmetric self-play, and/or intrinsic motivation.
- You will own a focused research project, work closely with Vmax technical staff, and contribute to research publications.
- A core focus of ours is agents that can learn to find their own objectives in the world.
Requirements
- Strong programming ability in Python and experience with at least one major ML framework such as PyTorch or JAX.
Nice to have
- Experience with LLM post-training methods
- Experience with scalable ML experimentation, distributed training, experiment tracking, or reproducible research infrastructure.
- Demonstrated taste for identifying non-obvious research directions and converting them into tractable experiments.
- This role is based in our San Francisco office
Benefits
- Design systems for open-ended learning, including unsupervised/automated environment design, asymmetric self-play, and intrinsic motivation.
- Currently enrolled in a PhD program in machine learning, computer science, artificial intelligence, computational neuroscience, mathematics, or a related technical field.
- Working understanding of reinforcement learning.
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.