Member of Technical Staff - Platform Engineering

1 нед. назад

200k–275k USD / yearUSALeadOnsite

reinforcement learningpythoninfrastructuredata pipelines

Platform engineer role building RL environments and infrastructure for AI agents in financial services at .

Base: $200–275k · Equity: 0.15–0.30% · Location: San Francisco, 5 days in office
Own platform engineering, develop frontier long-horizon RL environments, and help build our engineering org from the ground up.
Build our RL environment training and inference infrastructure to support customer usage at scale.
Research and develop next-generation RL environments — increasingly realistic, long-horizon, and difficult for frontier models.
Build software that 10–100x's the quality and throughput of RL environment creation.
Innovate on synthetic data pipelines to create realistic problems.
Build platform analytics for environment cost, hours, bottlenecks, and SME management.
Craft domain-specific verifiers (verifiable rewards for decks, Excel modeling, quantitative trading, and beyond).
Establish engineering culture and practices from the ground up.

Healthcare — Fully covered medical, dental, and vision for you. Subsidized for dependents.
Relocation — $10k+ relocation stipend to help you get to San Francisco.
401(k) — Up to 4% employer match.
Food — Free breakfast, lunch, and dinner while working.
Health — Free gym membership.
Transportation — Free Ubers and Waymo rides to and from the office.
Visa sponsorship — We sponsor visas, including H-1B.

is an applied AI and data company building computer-use and tool-use RL gyms to train AI agents on real financial services work — Excel modeling, pitch decks, and everything investment banking, private equity, and hedge funds rely on. We work with frontier labs, graduated from Y Combinator (S25), and raised a seed round to scale the team.
Familiarity building evaluations, benchmarks, or RL for AI agents.
Startup speed: iterate quick, ask quick, respond quick, make mistakes quick.
Strong product and user ownership; ability to prioritize across a large roadmap.
Client-facing comfort — you'll talk to users, customers, and SMEs.