Jobs Companies Mind Robotics Controls Engineer

Sobre esta vaga de Controls Engineer na Mind Robotics

Mind Robotics · Presencial · Palo Alto

The Role

At Mind Robotics, we're building generalized physical AI — robotic systems capable of dexterous, adaptive, and reasoning-intensive work in real-world industrial environments. Controls is where intelligence becomes motion: the layer that translates high-level commands into precise, safe, and coordinated physical behavior across every joint and actuator on the robot.

We're looking for a Controls Engineer to own the algorithms and software that make our robots move well — from low-level actuator loop design to full-body motion control and the simulation infrastructure that keeps us iterating fast.

Responsibilities

  • Design, implement, and tune control algorithms — PID, state-space, model-based, and beyond — for joints, actuators, and whole-body robot motion

  • Develop and maintain high-fidelity dynamic models of robot subsystems to support simulation, analysis, and controller design

  • Analyze real-world robot data to assess controller performance, identify regressions, and drive targeted improvements

  • Work closely with firmware engineers to implement control algorithms under hard real-time constraints in C/C++ or Rust

  • Collaborate with mechanical and electrical engineers to characterize hardware, close the loop between physical design and software performance, and define actuation requirements

  • Define and execute test plans that validate control system performance across the full operating envelope of the robot

Qualifications

  • M.S. or Ph.D. in controls, robotics, or a related field, or equivalent hands-on experience building and deploying control systems for real physical hardware

  • Demonstrated experience (through work, research, or projects) designing and deploying control systems for real physical systems — robots, actuators, drones, or similar

  • Strong foundation in control theory: classical (PID, lead-lag), modern (state-space, LQR/MPC), and familiarity with nonlinear systems

  • Experience building dynamic models and using simulation tools (MATLAB/Simulink, Python, Julia, or equivalent) to inform and validate controller design

  • Hands-on experience tuning controllers on real hardware and debugging unexpected behavior with real data

  • Proficiency in C/C++ or Rust for real-time control implementation

  • You are comfortable with ambiguity, move fast, and have an "engineering curiosity" that drives you to understand how the entire system works, not just your part

Nice to Have

  • Experience with whole-body control, trajectory optimization, or model predictive control on legged or manipulator systems

  • Familiarity with field-oriented control (FOC) or other motor control algorithms at the firmware level

  • Exposure to functional safety standards (ISO 26262, IEC 61508, or similar)

  • Experience with ROS2 or similar robotics middleware

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