RL Specialist

We are seeking a highly skilled Reinforcement Learning specialist with expertise in planning and control.

• Develop and train policies from human demonstrations and teleoperation data.
• Implement safe reinforcement learning approaches with constraints.
• Design long-horizon planners using world models and uncertainty-aware control.
• Implement safety shields, fallback controllers, and verify-before-deploy pipelines.
• Collaborate with cross-functional teams to integrate RL policies with control systems.
• Conduct sim-to-real transfer and ensure policies generalize in real-world settings.
• Design reward functions and implement offline RL and behavioral cloning strategies.

• 4–8+ years of experience in RL and control systems.
• Strong expertise in Model Predictive Control (MPC), Control Barrier Functions (CBFs), reachability analysis, or similar methods.
• Master's or PhD in Robotics, Control, AI, or a related field.
• Experience with sim-to-real transfer, reward design, offline RL, and behavioral cloning.

• Humanoids: Stable locomotion and bimanual task RL.
• AGVs (Autonomous Ground Vehicles): Navigation in mixed human zones, traffic rule compliance, and aisle etiquette.
• Cars: Interactive merges, handling unprotected turns, and safe navigation in dynamic traffic.
• Drones: Wind-robust flight, safe landing and perching maneuvers.