Job Description

Senior Research Scientist - San Francisco or Redwood City

A company who are building AI systems with general physical ability are looking for Senior Reinforcement Learning Research Scientist to build reinforcement learning systems that drive real-world experimentation and tool orchestration.

What Will I be Doing:

• Create and maintain RL environments for optimizing tools, experiments, and process workflows using both simulations and digital twins.
• Develop safe RL strategies, reward structures integrated with verifiers, and frameworks for moving from offline training to robust online behavior.
• Define state and action representations and enforce constraints for reliable, long-horizon decision-making.
• Partner with LLM researchers, agent engineers, and simulation teams to integrate RL agents into live experimental systems.

What We're Looking For:

• Expertise in reinforcement learning, optimal control, or sequential decision-making, with experience applying RL to complex real or simulated systems.
• Familiarity with safe RL, constrained RL, verifier/detector integration, or multi-step policy evaluation frameworks.
• Demonstrated ability to build RL environments, design reward structures, and diagnose policy behavior at scale.
• Comfortable working across ML, simulation, systems engineering, and physical-toolchain interfaces in a fast-paced research environment.

What’s in It for Me:

• $200-$300k and meaningful equity
• Ownership of cutting-edge RL systems deployed in real-world experimental workflows
• Work at the cutting edge of AI, robotics, and experimental science
• Contribute to building the world’s first physical superintelligence

Apply now for immediate consideration!

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