Gait Control Engineer

Shift Robotics•Austin, TX

35d

About The Position

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.

Requirements

MS or PhD in Robotics, Mechanical Engineering, Electrical Engineering, or related field
2+ years experience developing control algorithms for:
wearable robotics
legged robots
powered prosthetics
exoskeletons
humanoid locomotion
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

Nice To Haves

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.

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.
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.
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.
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.
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.