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!
Job Tags
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