Physical Intelligence
Controls Engineer
San Francisco
Sponsorship not specifiedDetected 196 days ago
PythonC++AlgorithmsEmbedded SystemsResearchCommunication
About the role
- 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.
- 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.
- Ability to validate control approaches in simulation and translate them to real hardware
- Ability to design or refine custom actuator or sensor hardware
- 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.
Requirements
- Proficiency in Python and C++, including firmware-adjacent development
Benefits
- Exposure to robot learning or integrating learned policies into control stacks
- Bonus Points If You Have
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This listing is sourced directly from Physical Intelligence's careers page and normalized into a canonical job model.