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Computer Vision • Hardware • Machine Learning • Robotics • Software
Develop accurate simulation abstractions for tendon-driven robotic hands and validate them against physical hardware through system identification, actuator characterization, calibration, and testing. Own the sim-to-real pipeline for transferring reinforcement learning policies to hardware, including dynamics modeling, domain randomization, friction and backlash characterization, and control tuning. Lead technical execution autonomously and collaborate with reinforcement learning and controls teams to resolve simulation-to-reality discrepancies.
Computer Vision • Hardware • Machine Learning • Robotics • Software
Lead electromagnetic design of custom BLDC and PMSM motors for humanoid robot joints from concept through prototype and volume manufacturing. Perform advanced simulations, define motor performance targets, validate designs using motor dyno testing, and correlate models with hardware. Collaborate with mechanical, thermal, electrical, controls, manufacturing, vendors, and university partners to optimize torque density, ensure design-for-manufacturing, manage technical requirements, and support technology transfer.
Computer Vision • Hardware • Machine Learning • Robotics • Software
Leads a team developing real-time control software for humanoid robots. Responsibilities include hiring and mentoring engineers, managing controls roadmap delivery, reviewing designs and code, maintaining testing and release quality, validating simulation-to-hardware performance, and collaborating with firmware, embedded software, learning, teleoperation, systems, and test teams. The role requires hands-on expertise in robot controls, C++ real-time software, physical robot deployment, and engineering leadership.
