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Physical Intelligence Logo Physical Intelligence · IT - Software Development

Controls Engineer

United States, San Francisco · Job Posted February 21, 2026
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Job Description

Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future. As a Controls Engineer, you will design and implement the algorithms that make PI’s robots behave predictably, smoothly, and safely under varied and uncertain conditions.

Job Responsibility

  • 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

Nice to have

  • 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
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