System Identification & Controls Engineer

About the Company

At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society.

Responsibilities

• Plan and run system identification across all Skild robot platforms including actuators, transmissions, joints, rigid-body dynamics, and sensors
• Design excitation trajectories and bench/on-robot tests
• Characterize actuators and motors on dynamometers, test benches, and hardware-in-the-loop setups
• Fit dynamics models, quantify accuracy, and close the sim-to-real gap
• Apply classical controls including state estimation, calibration, stability and bandwidth analysis to real hardware
• Build automated pipelines to scale identification from a single robot to the whole fleet
• Quantify unit-to-unit variation and track drift and wear over time
• Set the standard and tooling for system identification and document findings rigorously

Requirements

• Demonstrated hands-on track record of system identification on real robotic or electromechanical hardware
• Strong classical controls foundation including feedback/feedforward, cascade control, frequency-response, and stability analysis
• Solid grasp of robot hardware and mechatronics such as motors, transmissions, encoders, IMUs, and force-torque sensors
• Practical experience with excitation design, hardware data collection, and parameter estimation
• Proficiency in Python and C++ in a Linux environment

Preferred Qualifications

• MS or PhD in Mechanical/Electrical Engineering, Controls, Robotics, Aerospace, or a related field
• MATLAB/Simulink proficiency
• Familiarity with robotics dynamics tooling and simulators like MuJoCo, Isaac Sim, Drake, Pinocchio, or ROS/ROS2
• Experience deploying calibration or controls across a large fleet of robots or vehicles