Gait Control Engineer

About Shift Robotics We're making the world a more walkable place. Through intuitive personal mobility, we make walking faster, more efficient, and more accessible to empower people to choose walking over sitting in traffic. By giving people the ability to Moonwalk, we believe the path forward to a better future is easily reached on your own two feet.

Our flagship product, Moonwalkers, are the world?s fastest robotic shoes, augmenting natural walking with intelligent locomotion assistance. By giving people the ability to Moonwalk, we believe the path toward a more human-scale future can be reached on your own two feet.

We are building the next generation of Moonwalkers and are looking for engineers who thrive in fast-paced environments where hardware, software, and human motion intersect.

We are covered in Wired, CNET, Gizomodo, PCMag and many other tech press.

Role Overview The Gait Control Engineer will lead the development of locomotion control algorithms for Shift?s robotic footwear platform. This role focuses on designing, implementing, and deploying robust control and estimation algorithms that enable safe, intuitive, and responsive human-machine interaction.

You will work closely with mechanical, electrical, and firmware teams to develop algorithms that run reliably on embedded systems while handling real-world variability in human gait and terrain.

This role requires strong intuition for human locomotion, control systems, and embedded algorithm implementation.

Responsibilities: Locomotion Control Development

• Design and implement gait control algorithms for wearable robotic systems.
• Develop control strategies for walking assistance across different user speeds, terrain conditions, and gait phases.
• Implement and validate locomotion controllers on embedded hardware. </li></ul> State Estimation & Sensor Fusion
  • Develop real-time estimation algorithms using IMU, force sensors, encoders, and other onboard sensors.
  • Implement sensor fusion pipelines for gait phase detection, motion estimation, and intent recognition.
  • Ensure algorithms remain robust under noisy real-world conditions. </li></ul> Algorithm Prototyping & Validation
    • Prototype algorithms in Python or MATLAB?before deploying to embedded systems.
    • Evaluate control strategies using simulation tools (e.g., MuJoCo, Simulink, or custom simulation environments).
    • Design experiments and analyze data from real hardware testing. </li></ul> Embedded Implementation
      • Translate algorithms into efficient C/C++ implementations?for real-time embedded systems.
      • Optimize algorithms for low-latency execution on resource-constrained processors.
      • Work with firmware engineers to integrate control algorithms into production software. </li></ul> System Integration
        • Collaborate with mechanical and electrical engineers on actuator selection, sensor placement, and system architecture.
        • Ensure control algorithms meet performance, safety, and reliability requirements.
        • Identify system limitations and propose improvements in hardware or software.
        Requirements Education:
        • MS or PhD in Robotics, Mechanical Engineering, Electrical Engineering, or related field

        Experience:

        2+ years experience developing control algorithms for:
        • wearable robotics
        • legged robots
        • powered prosthetics
        • exoskeletons
        • humanoid locomotion

          </li></ul> Technical Skills:

          • Strong understanding of:
          • Control systems
          • Multibody dynamics
          • Human locomotion
          • State estimation
          • Sensor fusion
          Experience with:
          • Real-time control implementation in C/C++
          • Algorithm prototyping using Python or MATLAB
          • Embedded systems development
          • Processing IMU and force sensor data
          • Debugging real-time robotic systems

          Preferred Qualifications:

          Experience with one or more of the following:
          • Gait phase detection and intent recognition
          • Model-based control (e.g., MPC, optimal control)
          • Extended Kalman Filters or nonlinear state estimation
          • RTOS-based embedded systems
          • ARM Cortex microcontrollers
          • Real-time signal processing
          • Simulation tools such as MuJoCo, Simulink, or OpenSim
          • Experience working on production robotics systems or shipping hardware products is highly valued.
          Benefits
          • Competitive salary and equity participation
          • 401(k) retirement plan
          • Medical, dental, and vision insurance
          • Flexible vacation policy
          • Paid holidays
          • A collaborative, fast-moving engineering environment
          • Opportunity to shape the future of personal mobility