Gait Control Engineer

Shift Robotics; Austin (TX); On-site; USD 85,000 - 120,000; Full time

Benefits offered by this job

Competitive salary and equity participation

401(k) retirement plan

Medical, dental, and vision insurance

Flexible vacation policy

Paid holidays

Job summary

Shift Robotics is seeking a Gait Control Engineer in Austin, Texas, to lead the development of locomotion control algorithms for innovative robotic footwear. The role involves designing and implementing algorithms for safe and intuitive human-machine interaction and requires collaboration with mechanical, electrical, and firmware teams.

The ideal candidate will possess a strong background in control systems, human locomotion, and embedded algorithm implementation with advanced degrees in Robotics or Engineering.

Qualifications

• 2+ years of experience developing control algorithms for wearable robotics.
• Experience in real-time control implementation for embedded systems.
• Strong understanding of multibody dynamics and human locomotion.

Responsibilities

• Design and implement gait control algorithms for robotic systems.
• Develop real-time estimation algorithms and sensor fusion pipelines.
• Collaborate with engineers for actuator selection and system integration.

Skills

Control systems

State estimation

Sensor fusion

Embedded systems

C/C++ programming

Python

MATLAB

Education

MS or PhD in Robotics or related field

Tools

MuJoCo

Simulink

Job description

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.
• 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 (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.

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, or humanoid locomotion.
• Technical Skills: Strong understanding of control systems, multibody dynamics, human locomotion, state estimation, and 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 gait phase detection and intent recognition; model‑based control (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