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Reinforcement Learning Engineer Salary Jobs (NOW HIRING)

Skild AI

Machine Learning Engineer

San Mateo, CA

$100K - $300K/yr

Machine Learning Engineer San Mateo, Pittsburgh Company Overview At Skild AI, we are building the ... Extensive industry experience with reinforcement learning and robotic systems. Base Salary Range ...

Skild AI

Machine Learning Engineer

Pittsburgh, PA

$100K - $300K/yr

Machine Learning Engineer San Mateo, Pittsburgh Company Overview At Skild AI, we are building the ... Extensive industry experience with reinforcement learning and robotic systems. Base Salary Range ...

Centific

Applied Reinforcement Learning Engineer

Applied Reinforcement Learning Engineer Location: Palo Alto, CA or Seattle, WA (Hybrid/Remote ... Salary: $150K - $300K Annually Centific is an equal-opportunity employer. All qualified applicants ...

Skild AI

Machine Learning Engineer

San Mateo, CA

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...

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How much do reinforcement learning engineer salary jobs pay per year?

As of Jun 9, 2026, the average yearly pay for reinforcement learning engineer salary in the United States is $115,864.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,000.00 and $151,500.00 per year, depending on experience, location, and employer.

What is the difference between Reinforcement Learning Engineer Salary vs Machine Learning Engineer Salary?

Reinforcement Learning Engineer SalaryMachine Learning Engineer Salary
Average salary varies based on experience, location, and industry, typically ranging from $100,000 to $150,000 annually.Average salary also varies widely, generally between $90,000 and $140,000 annually, depending on similar factors.

Both roles require strong programming skills, knowledge of machine learning frameworks, and experience with data analysis. Reinforcement Learning Engineers focus specifically on developing algorithms for decision-making tasks, while Machine Learning Engineers work on broader AI models. Salaries are comparable, with Reinforcement Learning Engineers often earning slightly more in specialized industries.

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Reinforcement Learning Engineer Salary jobs near you
Infographic showing various Reinforcement Learning Engineer Salary job openings in the United States as of June 2026, with employment types broken down into 94% Full Time, 2% Part Time, and 4% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $115,864 per year, or $55.7 per hour.
Reinforcement Learning Engineer ($400k - $800k salary)

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

Baton

Farmington, NY

$400K - $800K/yr

Other

Posted 15 days ago

Job description

Reinforcement Learning Engineer

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