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Responsibilities
- Develop and optimize a learning-based robotic manipulation control stack.
- Design and maintain a teleoperation system with smooth, precise motion and low latency.
- Train robotic policies for manipulation and locomotion using reinforcement and imitation learning.
- Deploy robotic policies and diagnose latency or bottlenecks in the control pipeline.
- Analyze and minimize the sim-to-real gap by co-optimizing simulation and real-world robot behavior.
- Collaborate with a team committed to building general-purpose Physical AI.
Requirements
- Passion for your craft and demonstrated excellence in robotics engineering.
- Exceptional ownership and initiative; find and solve problems independently.
- Focus, attention to detail, patience, and a methodical approach to complex tasks.
- Production-level expertise in modern Python or C++.
- Extensive experience building and deploying real-world learning-based robotic systems (5+ years).
- Hands-on experience troubleshooting and maintaining robotic systems across mechanical, electrical, and software components.
Skills
- Python
- C++
- Robotics
- Reinforcement Learning
- Imitation Learning
- Robotic Manipulation
- Teleoperation
- Control Systems
- Simulation
- Physical AI
Experience Level
- 5+ years of experience building and deploying real-world learning-based robotic systems