Intern - Robotics Engineer

About the role#

Human Computer Lab is seeking a Robotics Engineer Intern to join our Controls team. This role focuses on the systems that allow our robots to move and respond with intentionality. You will work at the intersection of hardware and software, bridging the gap between low-level motor control and high-level expressive behaviors. This is a hands-on position requiring direct work with physical hardware to translate design intent into fluid motion.

What you'll do#

• Design and tune control systems for actuated subsystems, focusing on motion control, feedback, and dynamic response.
• Integrate actuators, sensors, encoders, and embedded electronics into reliable mechatronic assemblies.
• Develop control algorithms in C++ and/or Python, moving from simulation to hardware deployment.
• Build and maintain URDF models and simulation environments that align with the physical platform.
• Diagnose and resolve real-world control issues, including instability, backlash, latency, drift, and sensor noise.
• Collaborate with animators, mechanical engineers, and electrical engineers on actuator selection, sensing strategies, and motion fine-tuning.
• Develop motion primitives and expressive behaviors that shape robot movement.
• Maintain documentation of control architecture and tuning decisions throughout the development process.

What you'll need#

• Currently pursuing a Bachelor's or Master's degree in Electrical Engineering, Mechatronics Engineering, Software Engineering, or Computer Science.
• Hands-on experience tuning control systems on real robotic hardware.
• Proficiency in C++ and/or Python for robotics or embedded control.
• Experience with ROS or ROS2 and real-time robotics software stacks.
• Experience building URDF models and working with simulators such as Gazebo, MuJoCo, or Isaac Sim.
• Familiarity with CAD tools such as SolidWorks or Onshape.
• Experience with actuators, motor drivers, encoders, and IMUs.
• Proficiency in hardware debugging using tools like oscilloscopes and signal tracing.
• Experience with impedance control, torque control, or whole-body control.
• Knowledge of sensor fusion, state estimation, or Kalman filtering.
• Experience with embedded programming on microcontrollers or DSPs.

Location & details#

• Location: San Francisco, California
• Modality: Remote and Hybrid
• Term: Rolling