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Dexmate

Robot type
Humanoid
Location
FremontCaliforniaUSA
Job type
Hardware
Posted
Feb 28, 2025
Salary
$100,000–$300,000 a year
Full-time

Senior Robotics Controls Engineer

Job description

If you want to help shape the next layer of human capability — and believe the future of robotics should be built together, not in isolation — we'd love to build it with you.

Dexmate is building the foundation for physical AI — combining a new generation of robots with a universal Physical AI OS, making robots as easy to build and deploy as software. Today, robotics is fragmented, slow, and closed: most builders are forced to reinvent the same stack again and again, and most ideas never make it past the prototype stage. We exist to change that.

Job responsibilities

  • Design, implement, and deploy state estimation and sensor fusion algorithms for real-time general-purpose robot control — EKFs, UKFs, particle filters, factor graphs — fusing IMUs, encoders, force/torque sensors, and…
  • Develop and tune advanced control algorithms for dynamic robot motion: nonlinear control, model predictive control (MPC), optimal control, and whole-body control for legged and manipulating systems
  • Architect and ship production-grade C++ control code running in real-time embedded environments; hold your implementations to the same quality bar as deployed software
  • Iterate rapidly between simulation and hardware — design experiments, collect data, debug failure modes, and drive measurable performance improvements on physical robots
  • Develop trajectory optimization and motion planning algorithms that respect actuator limits, contact constraints, and stability margins
  • Define and maintain performance metrics and evaluation frameworks for control and estimation subsystems; own the failure analysis loop
  • Work directly with embedded, mechanical, and AI teams to integrate control algorithms across the full robot stack

Job requirements

  • 5+ years of professional experience developing control systems for dynamic robots, deployed on real hardware
  • Master's or PhD in Robotics, Controls, Mechanical Engineering, or related field
  • Deep expertise in control theory: nonlinear control, MPC, LQR, optimal control, and whole-body control
  • Strong state estimation background: Kalman filters (EKF/UKF), particle filters, factor graphs, and Bayesian estimation
  • Production-quality C++ for real-time control; Python for analysis, simulation, and tooling
  • Solid command of robot kinematics, rigid-body dynamics, and spatial mathematics
  • Hands-on experience with sensor integration and characterization: IMUs, encoders, force/torque sensors
  • Proven track record implementing and validating control algorithms on physical robotic systems — not just simulation
Apply on Dexmate websiteSave

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