Senior Locomotion Control Engineer

About the Company

Faraday Future (FF) is a California-based embodied artificial intelligence ecosystem company, leveraging the latest technologies and world’s best talent to realize exciting new possibilities in mobility and robotics.

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

Requirements

• 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 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

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

• Healthcare, dental, and vision benefits
• 401(k) options