Head of Research
Operations
United States · San Francisco, CA, USA · Bergen, Norway
Posted on Jul 7, 2026
About Traverse
Traverse is a research data lab building reinforcement learning environments for frontier AI labs. We focus on the non-deterministic, taste-dependent work that makes up most of the economy and that nobody else has figured out how to train models on. We work directly with the labs building the most capable models on earth as a thought partner. Backed by Y Combinator.
About the Role
As Head of Research, you will define and lead the research agenda that determines how we build RL environments for domains where mastery is ambiguous and feedback is hard to formalize. You will be the person who figures out how to encode what "good" looks like in fields like medicine, law, engineering, and negotiation, and turns those insights into environments that actually make models better. This role sits at the intersection of research and domain expertise. You will work directly with the frontier labs we partner with, understand their training pipelines and needs, and ensure that what we build reflects real hypotheses about how intelligence develops in a given domain. No prior ML or AI experience is required - we value rigorous thinkers from any research discipline who can reason about hard problems from first principles.
In this role, you will
- Set the research direction for how Traverse builds and evaluates RL environments across verticals
- Develop methodologies for encoding domain expertise into reward signals, evaluation criteria, and environment design
- Work directly with partner labs to understand their post-training pipelines and co-design environments
- Hire and lead a team of research scientists
- Publish and present work that establishes Traverse as a serious research institution
Your background looks something like this
- PhD or equivalent depth of research experience in any rigorous field
- Track record of original work on hard, open-ended problems
- Ability to lead a team and set a research agenda
- Strong opinions and the ability to defend them
Bonus
- Published work in reinforcement learning, RLHF, reward modeling, or LLM post-training
- Deep expertise in a non-ML domain (medicine, law, finance, engineering) in addition to or instead of ML
- Prior work at a frontier AI lab
Compensation
Negotiable - Offers Equity