Senior Locomotion Control Engineer

Your Role

We are seeking a Senior Locomotion Control Engineer to lead the design, implementation, and real-world deployment of robot motion capabilities. This role is responsible for building robust locomotion systems that work reliably across simulation and hardware, and for driving the technical direction of gait, balance, terrain adaptation, and control integration.

Responsibilities

• Design, implement, and optimize robot locomotion systems, including gait generation, balance control, and terrain adaptation.
• Develop and improve locomotion controllers using MPC, whole-body control, reinforcement learning, or hybrid control approaches.
• Own the full loop from simulation to hardware deployment, including controller tuning, regression validation, and failure analysis.
• Improve robot stability, robustness, safety, and energy efficiency in real-world operating conditions.
• Work closely with runtime, simulation, behavior, and hardware teams to define clean interfaces and reliable integration paths.
• Support real-robot bring-up, debugging, performance analysis, and root-cause investigation for motion failures.
• Contribute to control architecture decisions, testing methodology, and technical roadmap planning for motion control capabilities.

Basic Qualifications

• Master's degree or above in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, or a related field.
• 5+ years of experience developing robotics locomotion, motion control, or autonomous robotic systems.
• 3+ years of hands-on experience supporting quadruped, humanoid, or legged robot development and deployment.
• Strong foundation in robotics, including dynamics, kinematics, estimation, and control theory.
• Hands-on experience with at least one locomotion approach such as MPC, whole-body control, reinforcement learning locomotion, or heuristic gait control.
• Strong C++ skills for production robotics software development.
• Proficiency in Python for research workflows, simulation, tooling, and analysis.
• Experience deploying algorithms on real robots, ideally quadrupeds, humanoids, or mobile manipulation systems.
• Prior experience deploying locomotion or control algorithms on physical robots is required.
• Ability to diagnose real-system failures and translate observations into actionable control or systems improvements.

Preferred Qualifications

• Experience with RL locomotion, imitation learning, or policy-based control for physical robots.
• Experience with sim-to-real workflows, including actuator modeling, latency compensation, domain randomization, or system identification.
• Familiarity with MuJoCo, Isaac, RaiSim, Gazebo, or equivalent simulation platforms.
• Experience with real-time robotics systems, ROS 2, controller scheduling, and control-runtime integration.
• Background in contact-rich control, force control, or whole-body coordination.
• Track record of shipping motion capabilities from prototype to robust field performance.

Benefits

($110,000 - $135,000 DOE), plus benefits and incentive plans:

Perks + Benefits

• Healthcare + dental + vision benefits (Free for you/discounted for family)
• 401(k) options
• Casual dress code + relaxed work environment
• Culturally diverse, progressive atmosphere