Staff / Principal Research Scientist

Who We're Looking For

A year ago, reliably working agentic systems barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood.

Experience We Find Useful

You don't need all of this. But you need enough to make a case.

Foundation models: training, new architectures, RL, reward modeling, scaling

Evaluation: benchmarks, eval loops, quality measurement, LLM-as-judge, failure analysis

Frontier topics: multimodal models, agents, tool use, test-time compute, world models

Published research at ICML, ICLR, NeurIPS, EMNLP, ACL, or AAAI

PhD in ML/NLP — or equivalent practical experience you can point to

Public work: non-trivial AI side projects, interdisciplinary experiments, open-source contributions

Full-stack research ownership: you frame the question, run the experiments, write the paper, ship the result

If you learned through building, competitions, or collaborations outside academia, that counts. We care about evidence, not credentials.

Who Thrives Here

You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go

You believe research isn't finished until it’s shipped. You have a bias for impact over purely academic output

You don't just ship code; you obsess over the why. You’re the first to question an approach if you think there’s a better way to solve the core problem

You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make

What Working Here Is Like

We hand you unclear problems and expect you to make them clear. We value researchers who say "I don't know yet" and then design the experiment that finds out. We treat evaluation as a first-class research product, not a box to check before launch. Impact comes before publications though we support sharing work that moves the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater.

We believe in the power of in-person collaboration to solve the hardest problems and foster a strong team culture. We offer relocation assistance and look forward to you joining us in our Mountain View office.