Employer profile
Traverse
4 open roles indexed with location, benefit, and apply-link signals where available.
Open roles
Showing the most recent indexed roles for this employer.
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Founding Engineer
San Francisco | OnSite
onsite Salary not disclosedFounding Engineer San Francisco | OnSite 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 a Founding Engineer, you will build the core infrastructure and environments that train AI models to do tasteful work. You'll operate across the full stack, from designing reward functions and evaluation pipelines to building the tooling that lets us scale environment quality across new domains without it falling apart. This is not a narrowly scoped role. You'll work on whatever matters most, and what matters most changes as we move into new domains and take on new lab partnerships. We care about raw engineering ability and taste, not credentials or keywords on a resume. No prior ML or AI experience is required. IN THIS ROLE, YOU WILL - Design and build RL training environments across multiple verticals, working closely with domain experts and AI Researchers - Build infrastructure and tooling that enables environment quality to scale across domains - Work directly with frontier AI labs to understand their training pipelines and integrate our environments into their workflows - Own problems end-to-end, from scoping through implementation through evaluation - Shape the technical direction of the company as an
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Research Scientist
San Francisco | OnSite
onsite Salary not disclosedResearch Scientist San Francisco | OnSite 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 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. IN THIS ROLE, YOU WILL - 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
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Research Intern
San Francisco | OnSite
onsite Salary not disclosedResearch Intern San Francisco | OnSite 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 a Research Intern, you will work alongside the research team to design and evaluate RL environments for domains where expertise is hard to formalize. You'll get hands-on experience at the frontier of AI training, contributing to projects that ship directly to partner labs. This is a high-impact internship for someone who learns fast, thinks carefully, and wants to do work that matters. We prefer individuals with prior ML or AI experience, however we care more about intellectual curiosity and the ability to reason rigorously about hard problems. IN THIS ROLE, YOU WILL - Assist in designing and evaluating RL environments across new domains - Run experiments to test hypotheses about reward modeling and environment quality - Collaborate with domain experts to understand what mastery looks like in a given field - Contribute to internal research documents and help refine Traverse's methodology - Work directly with research scientists and engineers on active projects YOUR BACKGROUND LOOKS SOMETHING LIKE THIS - Currently pursuing or recently completed a BS, MS, or PhD in any rigorous field - Strong analytical and
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Head of Research
San Francisco | OnSite
onsite Salary not disclosedHead of Research San Francisco | OnSite 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 own the entire research function at Traverse, from setting the agenda and publishing papers to building benchmarks and leading the team that figures out how to train AI on the hardest problems in the world. The core challenge is that most of the economy runs on work where "good" is subjective, feedback is delayed, and expertise takes decades to develop. Medicine, law, negotiation, engineering: none of these domains have neat reward signals, and figuring out how to encode what mastery looks like in these fields and turn that into RL environments that actually make models better is an open research problem. You'll be the person solving it. You'll work directly with the frontier labs we partner with, understand their post-training pipelines, and co-design environments that reflect real hypotheses about how intelligence develops in a given domain. You'll publish novel work that establishes Traverse as a research institution, not just a data vendor. We're looking for someone with serious research depth in ML and a track record of publishing at top venues,