Research Scientist

Traverse•San Francisco, CA

About The Position

As a Research Scientist, you will design and build RL environments that teach models to do work that has historically required years of human expertise. You'll work at the boundary of research and domain knowledge, figuring out how to formalize what good performance looks like in messy, real-world domains and turning that into training signal that actually works. We're looking for people who think carefully about what makes a good environment, not just what makes a functional one. No prior ML or AI experience is required - we care about the ability to reason rigorously about hard problems and learn fast.

Requirements

MS, PhD, or equivalent depth of experience in any rigorous field
Strong implementation skills and ability to run experiments quickly
Genuine curiosity about domains outside your own and how expertise works in them
You go deep on problems and don't stop at the obvious answer

Nice To Haves

Experience with reinforcement learning, RLHF, reward modeling, or LLM evaluation
Published research in any field
Prior work at or with a frontier AI lab

Responsibilities

Research and develop novel approaches to reward modeling, environment design, and evaluation for non-deterministic domains
Collaborate with domain experts to understand what mastery looks like in a given field and translate that into training signal
Build and run experiments to validate that environments actually improve model capabilities
Contribute to Traverse's research output and help establish our methodology across new verticals
Work directly with partner labs to integrate environments into their post-training pipelines