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    Infographic showing various job openings at Baton in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% Physical job distribution.
    Reinforcement Learning Engineer ($400k - $800k salary)

    Reinforcement Learning Engineer ($400k - $800k salary)

    Baton Corporation Ltd

    New York, NY • On-site

    $400K - $800K/yr

    Full-time

    Posted 8 days ago

    Job description

    Who We Are
    Baton Corporation is the development company that builds and operates the entire technology stack behind pump.fun, the largest memecoin launchpad in production today. The systems are low latency, high throughput, live under constant load, and break if you get them wrong.
    What You'll Do
    As our Reinforcement Learning Engineer, you will own a production trading system that directly deploys real capital. This is not a research role - it's about building learning systems that are robust, measurable, and safe under real-world constraints.
    • Own and ship an RL-driven trading agent using real capital to increase trading volume and user participation in a memecoin ecosystem
    • Design reward functions and policies aligned with product goals while enforcing strict downside risk constraints
    • Build evaluation and validation frameworks (simulation, offline analysis) to minimize reliance on live sequential testing
    • Safely transition an existing heuristic-based production system toward learning-based approaches
    • Take end-to-end ownership and technical leadership as the sole RL expert, from data and modeling through deployment, monitoring, and safeguards

    Who You Are:
    • You have previously put an autonomous learning system into production that directly controlled capital, pricing, traffic, or resources and can explain what broke and how they fixed it
    • Have personally designed and enforced hard risk limits (capital caps, loss bounds, circuit breakers) in a live system, not just talked about "risk-aware objectives.
    • Have built a policy evaluation loop from scratch (simulators, replay, counterfactuals, shadow deployments) before trusting live rollout.
    • Can make and defend uncomfortable tradeoffs (e.g. heuristic > RL, bandit > deep RL) based on empirical results instead of ideology
    • Have operated as the single owner of a complex ML system in a small team, with no safety net of research orgs, infra teams, or "ML platforms."

    What it's like to work here
    • We work in person
    • Hours can be long and unconventional
    • The pace is intense
    • Expectations are high, and impact is immediate
    • Working at Baton is not for everyone

    Why Join Us?
    • Unmatched ownership and autonomy
    • Exposure to systems operating at the edge of crypto scale
    • The ability to ship fast and see real-world impact immediately

    If you're motivated by responsibility, speed, and building products used by massive audiences, you'll feel at home here.

    Apply