Member of Technical Staff - Open Endedness

Member of Technical Staff - Open Endedness About V max V max is an applied research lab working at the frontier of reinforcement learning (RL). We are building new techniques for leveraging RL with Large Language Models (LLMs). Our research contributes directly to our RL platform, which automates the engineering involved in converting data and evals into RL environments.

About the role Our goal is to automate the design of tasks for RL agents to help them learn domain specific skills. In this role you will develop approaches to optimize the construction of tasks to maximize resulting agent performance.

Responsibilities

Develop new approaches to task construction - building on literature in open endedness and unsupervised environment design

Develop new reward functions for environment design

Benchmark agents that learn in generated environments

Validate your research on industry specific problems

Role Requirements

AI PhD or equivalent experience

Track record of research excellence, as demonstrated by publications, open source work or publicly deployed AI systems

Deep understanding of RL and ML

Expertise with Python and an ML framework (PyTorch, JAX)

Nice to have

Experience in post-training LLMs

Experience researching evolutionary optimization

Experience researching unsupervised environment design

Skilled in presenting the results and implications of your work to multiple levels of audience

Role specific location policy

this role is based in our San Francisco office; for exceptional candidates we are willing to consider a hybrid arrangement

Compensation The expected salary range for this position is $250,000 - $450,000 USD

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