Dexmate

Dexmate

Senior Robotics control engineer

Santa Clara Office · Senior

Sponsorship not specifiedDetected 600 days ago
PythonC++AlgorithmsRoboticsMechanical DesignSensorsControls

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Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • 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.

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 proprioceptive signals
  • 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
  • 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
  • 5+ years of professional experience developing control systems for dynamic robots, deployed on real hardware
  • Define and maintain performance metrics and evaluation frameworks for control and estimation subsystems; own the failure analysis loop
  • 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.

Requirements

  • Deep expertise in control theory: nonlinear control, MPC, LQR, optimal control, and whole-body control
  • 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
  • Familiarity with trajectory optimization frameworks and solvers:
  • Proficiency with simulation environments:

Nice to have

  • Experience with bipedal, quadruped, or humanoid robots - highly dynamic, underactuated, contact-rich systems
  • Experience with whole-body control and contact dynamics: contact estimation, impact modeling, friction-cone constraints
  • Familiarity with trajectory optimization frameworks and solvers: OSQP, IPOPT, Crocoddyl, or custom implementations
  • Proficiency with simulation environments: MuJoCo, Drake, Isaac Sim, or equivalent
  • Experience with real-time computing constraints: deterministic execution, latency budgets, and embedded deployment
  • Track record of publications at top-tier venues (ICRA, IROS, CoRL, RSS, IJRR) is a strong plus

Company info

  • Our mission is to democratize robotics by lowering the barrier to entry, delivering a plug-and-play platform for developers, researchers, and enterprises, and cultivating an open ecosystem that accelerates the evolution of physical AI.
  • Dexmate is building the foundation for physical AI - a unified platform that combines high-quality robotic hardware with a universal Physical AI OS, making robots as easy to build and deploy as software.
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This listing is sourced directly from Dexmate's careers page and normalized into a canonical job model.