Controls Engineer

Posted 19 Hours Ago
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Palo Alto, CA, USA
In-Office
Mid level
Artificial Intelligence • Robotics • Industrial • Manufacturing
The Role
Design, implement, and tune control algorithms and dynamic models for robot joints and whole-body motion. Build simulation infrastructure, analyze real-world data, collaborate with firmware/mechanical/electrical teams, and validate control performance across the robots operating envelope.
Summary Generated by Built In

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

Skills Required

  • M.S. or Ph.D. in controls, robotics, or a related field, or equivalent hands-on experience
  • Demonstrated experience designing and deploying control systems for real physical systems (robots, actuators, drones, or similar)
  • Strong foundation in control theory: PID, lead-lag, state-space, LQR/MPC, and nonlinear systems
  • Experience building dynamic models and using simulation tools (MATLAB/Simulink, Python, Julia, or equivalent)
  • 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
  • Comfortable with ambiguity and strong engineering curiosity to understand system-level interactions
  • Experience with whole-body control, trajectory optimization, or MPC 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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The Company
20 Employees
Year Founded: 2025

What We Do

Mind Robotics builds intelligent, AI-driven robotic systems for industrial deployment, focusing on creating collaborative platforms for manufacturing environments.

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