Senior Robotics Controls Engineer

Roboticsconnected; Fremont (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Dexmate is building the foundational Physical AI OS for robots. We are seeking a Senior Robotics Controls Engineer to own state estimation and whole-body control for our robots.

You will design, implement, and ship real-time control algorithms in production C++ and iterate between simulation and hardware to achieve precise, stable motion. You will work with embedded, mechanical, and AI teams to integrate control across the stack, develop trajectory optimization, and define performance metrics to

Qualifications

• 5+ years of professional experience building control systems for dynamic robots on real hardware.
• Advanced degree (Master's or PhD) in Robotics, Controls, Mechanical Engineering, or related field.
• Strong state estimation background: Kalman/particle filters and Bayesian methods.
• Production-quality C++ for real-time embedded control; Python for analysis.
• Ability to deploy control algorithms end-to-end on physical robotic systems.

Responsibilities

• Design, implement, and deploy state estimation and sensor fusion algorithms for real-time robot control.
• Develop and tune advanced control algorithms for dynamic robot motion (MPC, nonlinear control).
• Architect and ship production-grade C++ control code in real-time embedded environments.
• Iterate rapidly between simulation and hardware; design experiments and drive measurable performance improvements on physical robots.
• Develop trajectory optimization and motion planning algorithms respecting 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 with embedded, mechanical, and AI teams to integrate control across the full robot stack.

Skills

State estimation

Sensor fusion

Real-time control

C++

Python

Embedded systems

Robotics control

Kinematics & dynamics

Education

Master's or PhD in Robotics/Controls/ME

Tools

MuJoCo

Crocoddyl

OSQP

IPOPT

Drake

Isaac Sim

Job description

ABOUT DEXMATE

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. Our mission is to democratise 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.

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.

THE ROLE

We are looking for a Senior Robotics Controls Engineer to own state estimation and whole-body control for our robots. You will design, implement, and ship real-time control and estimation algorithms in production C++, and iterate rapidly between simulation and hardware to make our robots move with precision and stability.

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
• 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

MINIMUM QUALIFICATIONS

• 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

PREFERRED QUALIFICATIONS

• Experience with bipedal, quadruped, or humanoid robots — highly dynamic, underactuated, contact-rich systems
• Background in reinforcement learning or learning-augmented control for legged locomotion or manipulation
• 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