Controls Engineer

About the Team

The Controls team builds and tunes the core feedback and model-based algorithms, real-time loops, simulations, and actuator/sensor subsystems that make PI’s robots stable and reliable. They work closely with research, hardware, and operations to debug complex system behaviors and ensure our learning-based systems operate under strict real-time constraints in unpredictable environments.

Responsibilities

• Design & implement control algorithms: PID, LQR, MPC, inverse dynamics, and feedforward controllers.
• Build & validate models: Create and refine physical and inverse dynamics models for simulation and control design.
• Develop real-time loops: Write and optimize runtime control loops, including neural-network-driven control.
• Own robotic bring-up: Integrate and tune arms, mobile bases, teleop systems, and full-body platforms.
• Debug complex system behaviors: Diagnose and resolve hardware/software/runtime issues using first-principles reasoning.
• Build sensor/actuator subsystems: Work with embedded systems, drivers, and communication protocols (CAN, SPI, I2C, Ethernet).
• Partner cross-functionally: Work with researchers, platform engineers, and operators to ensure stable, predictable real-world behavior.
• Support R&D: Prototype configurations, collect structured datasets, and iterate directly with researchers.

Requirements

• Deep understanding of model-based control algorithms and inverse dynamics
• Ability to validate control approaches in simulation and translate them to real hardware
• Proficiency in Python and C++, including firmware-adjacent development
• Skill in writing and tuning real-time control loops
• Hands-on capability to debug electromechanical systems end-to-end
• Familiarity with embedded communication protocols (CAN, SPI, I2C, Ethernet)
• Clear communication with researchers, hardware teams, and operators
• A structured, collaborative approach to solving complex system issues

Bonus Skills

• Background in manipulation or mobile robotic platforms
• Exposure to robot learning or integrating learned policies into control stacks
• Ability to design or refine custom actuator or sensor hardware