Member of Technical Staff, Robotics; Bay Area

Embedded Control Engineer

Design, implement, and optimize the embedded control stack for general-purpose robots

Design motion planning and trajectory optimization algorithms for dynamic locomotion and manipulation

Build real-time state estimation pipelines for pose, contact, and force sensing, fusing heterogeneous sensor data under noise and uncertainty

Formulate and solve optimal control problems (nonlinear MPC, convex optimization, trajectory optimization) for high-performance and stable behavior

Build modular and robust software frameworks enabling rapid iteration between simulation and hardware

Lead debugging, tuning, and validation of controllers directly on physical robots

Passion for your craft and demonstrated excellence in control systems engineering

Extensive experience in designing, implementing, and deploying advanced control algorithms on real robotic system products (8+ years)

Deep expertise in dynamics, kinematics, optimal control, and state estimation

Strong command of hardware interfaces, sensors (IMUs, F/T sensors), and actuation technologies (motors, gearboxes, drivers)

Production-level mastery of C++ with a track record of building reliable, safety-critical software

Proven ability to bridge across hardware, software, and algorithms to deliver robust end-to-end systems

An open mind about the power of deep learning, reinforcement learning, and vision-language-action models as critical for general-purpose robotics

Experience shipping humanoid robots or whole-body control systems

Impactful published work in control theory, state estimation, or mathematical optimization

Familiarity with parallel computation on GPUs to accelerate optimization