About Fleet Fleet studies how environments produce intelligence. We believe intelligence is an emergent property of environmental pressures: the environment determines what capabilities develop, what behaviors survive, and what "good" looks like.
About the role
About Fleet
Fleet studies how environments produce intelligence. We believe intelligence is an emergent property of environmental pressures: the environment determines what capabilities develop, what behaviors survive, and what "good" looks like. We work with frontier labs on post-training across modalities, building benchmarks that expose where frontier models break, training recipes that close those gaps, and scalable oversight for long-horizon agents. Backed by Sequoia Capital, Menlo Ventures, BCV, and SV Angel.
About the Role
We're looking for a Research Scientist to work on agentic RL post-training: the recipes that turn environment interaction into model capability. Tasks and environments are half the problem; the other half is training on them well. You'll train specialized agent models against Fleet's environments, scale the RL runs behind them, and own the algorithmic work that makes those runs pay off.
What You'll Work On
RL post-training recipes for multi-turn agents across modalities (tool use, browser use, terminal use)
Denser reward signals: verifiers, process supervision, richer feedback than binary outcomes
Scaling RL runs: larger models, longer horizons, many environments in a single run
Training specialized models that demonstrate what Fleet's environments teach
Algorithmic innovations in agentic RL, published where it makes sense
How We Work
You carry your own research threads that lead to concrete artifacts: a paper, benchmark release, training recipe, or open-source code
Direct collaboration with frontier labs
What We're Looking For
Hands-on experience post-training LLMs with RL, end-to-end
Publication record at top venues (NeurIPS, ICML, ICLR, or equivalent), or shipped training runs at comparable scale
High ownership: you manage your own research threads and are measured by what you produce
Location
San Francisco (on-site).
Compensation
Salary range: $200,000–$600,000 USD annually, plus meaningful equity.
Official source: fleetai.com. Details can change; the platform's page is the final word. How we check listings.
