Backed by General Catalyst, Khosla and Sequoia.
About the role
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.
What they're looking for
- 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
- Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records
More about this role
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.
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.
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...
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