At a Glance
- Tasks: Own and develop a production trading system using reinforcement learning for real capital.
- Company: Baton Corporation, the tech powerhouse behind pump.fun, the largest memecoin launchpad.
- Benefits: High salary, unmatched ownership, and immediate impact on innovative crypto systems.
- Other info: Intense work culture with high expectations and significant career growth opportunities.
- Why this job: Join a fast-paced environment where your work directly influences the memecoin ecosystem.
- Qualifications: Experience in deploying autonomous learning systems and enforcing risk limits in live environments.
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.
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. You 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.” You have built a policy evaluation loop from scratch (simulators, replay, counterfactuals, shadow deployments) before trusting live rollout. You can make and defend uncomfortable tradeoffs (e.g. heuristic > RL, bandit > deep RL) based on empirical results instead of ideology. You 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 Baton 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.
Compensation Range: $400K – $800K
Reinforcement Learning Engineer ($400k - $800k salary) employer: Baton Corporation
At Baton Corporation, we pride ourselves on being an exceptional employer that offers unmatched ownership and autonomy to our Reinforcement Learning Engineers. Located at the forefront of the crypto industry, our fast-paced work culture fosters innovation and immediate impact, allowing you to see the results of your efforts in real-time. With a focus on employee growth and the opportunity to work with cutting-edge technology, we provide a unique environment for those who thrive under pressure and are eager to make a difference.
StudySmarter Expert Advice🤫
We think this is how you could land Reinforcement Learning Engineer ($400k - $800k salary)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with Baton Corporation employees on LinkedIn. A personal touch can make all the difference when it comes to landing that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your previous projects, especially those involving autonomous learning systems or risk management. This will help you stand out and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for the interview by brushing up on real-world scenarios. Be ready to discuss how you've tackled challenges in past roles, especially around designing reward functions or enforcing risk limits. We want to see your problem-solving skills in action!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at Baton Corporation.
We think you need these skills to ace Reinforcement Learning Engineer ($400k - $800k salary)
Some tips for your application 🫡
Show Your Experience:Make sure to highlight any previous experience you have with autonomous learning systems. We want to see how you've put these systems into production and what challenges you faced along the way.
Be Specific About Risk Management:When discussing your background, be clear about the hard risk limits you've designed and enforced. We’re looking for concrete examples, not just theoretical knowledge, so share those real-world experiences!
Demonstrate Technical Leadership:As the sole RL expert, you'll need to take ownership of complex ML systems. In your application, showcase instances where you've led projects from data modelling to deployment, and how you navigated challenges without a safety net.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to see your application and get to know you better. Don’t miss out on the chance to join our fast-paced team!
How to prepare for a job interview at Baton Corporation
✨Know Your Stuff
Make sure you’re well-versed in reinforcement learning concepts and their practical applications. Be ready to discuss your past experiences with autonomous learning systems, especially how you’ve put them into production and what challenges you faced.
✨Showcase Your Risk Management Skills
Prepare to talk about how you've designed and enforced risk limits in live systems. Bring examples of hard risk constraints you've implemented and be ready to explain the rationale behind your decisions.
✨Demonstrate Technical Leadership
Since this role requires end-to-end ownership, highlight instances where you’ve taken charge of complex ML systems. Discuss how you’ve led projects from data collection to deployment, and how you ensured safety and reliability throughout the process.
✨Be Ready for Tough Trade-offs
Expect questions about making uncomfortable trade-offs in your work. Prepare to defend your choices between heuristic methods and RL approaches based on empirical results, showcasing your ability to make data-driven decisions.
