Reinforcement Learning Engineer

Bags.fm is the development company that builds and operates the entire technology stack behind bags.fm , the leading launchpad for new projects and ideas. The systems are low latency, high throughput, live under constant load, and break if you get them wrong.

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

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.”

We work in person

Hours can be long and unconventional

The pace is intense

Expectations are high, and impact is immediate

Working at Bags.fm is not for everyone

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.