
AI Research Planner
4 days ago
We are seeking an exceptional Reinforcement Learning (RL) professional with expertise in planning and control. The role focuses on developing learning-based planners and policies (RL, imitation learning, model-based) and integrating them with classical control approaches to enable safe, efficient, and robust autonomous operation across multiple domains including humanoids, AGVs, cars, and drones.
Key Responsibilities:- 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.
- 48+ years of experience in RL and control systems.
- Strong expertise in Model Predictive Control (MPC), Control Barrier Functions (CBFs), reachability analysis, or similar methods.
- Masters or PhD in Robotics, Control, AI, or a related field.
- Experience with sim-to-real transfer, reward design, offline RL, and behavioral cloning.
- Prominent roles in cutting-edge projects.
- Unlimited opportunities for growth and development.
- An engaging work environment that fosters collaboration and innovation.
- Task success rate in target domains.
- Rate of human or system interventions during execution.
- Compliance with energy, jerk, and other control limits.
- Minimization of constraint violations in real-world deployment.
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