Motion Planning and Controls Engineer
Develops motion planning and control software for AI robots, covering optimization algorithms, motor control, and electromechanical systems integration. Requires MS/PhD, expertise in Model Predictive Control, Python/C++, and multi-disciplinary problem-solving.
About the job
Responsibilities
- Cover the entire software stack that governs robot motion, from optimization-based motion planning and control for an overactuated autonomous system, down to individual motor torque control.
- Utilize deep expertise in complex, high degree-of-freedom electromechanical systems.
- Employ a multi-disciplinary mindset, bridging mechanical, electrical, software, and systems engineering domains.
- Interface with perception, intelligence, simulation, and platform software systems to design functional architectures for robot performance.
- Achieve exceptional motion quality via continual test, measurement, analysis, and improvement.
Must-have Qualifications
- MS or PhD in engineering, mathematics, computer science or related discipline.
- Experience in optimization-based motion planning and control algorithms such as Model Predictive Control.
- Experience in control, estimation, modeling, and analysis of complex multi-degree-of-freedom electromechanical systems, including forward/inverse kinematics, forward/inverse dynamics, and task/joint space control.
- Practical experience with motor servo control (position/velocity/torque control) architectures and tuning.
- Proficiency in Python and C++ programming, using up-to-date software development practices and tooling.
- Self-starter attitude with strong ability to identify problems, prioritize, plan and execute solutions.
- Enthusiasm for working in a fast-paced startup environment.
Nice-to-have
- Familiarity with ground vehicle localization, mapping, and state estimation techniques (e.g. SLAM, Kalman filtering).
- Familiarity with robotic simulation software frameworks/environments.
- Familiarity with modern approaches to robotic manipulation, including reinforcement learning (RL) and imitation learning (IL).
- Knowledge of brushless motor current control (e.g. field-oriented control).
- Familiarity with functional safety (FuSa) concepts.
Skills
Model Predictive Control, Python, C++, Forward Kinematics, Inverse Kinematics, Forward Dynamics, Inverse Dynamics, Motor Servo Control, Slam, Kalman Filtering, Reinforcement Learning, Imitation Learning, Field-Oriented Control
Similar jobs
Embedded Engineering jobs
OpenAI
San Francisco, CA
Design and implement real-time control infrastructure for intelligent, reliable robots, spanning actuators, hardware interfaces, state estimation, and whole-robot behavior. The role requires strong robotics and control fundamentals, hands-on hardware experience, and production-quality C++ or Rust development.
Fab2
Austin, TXOwn end-to-end software integration for semiconductor manufacturing equipment, spanning firmware, control software, electronics, actuators, testing, and production handoff. Requires 3+ years developing software for physical systems, proficiency in C, Rust, and Python, and strong hardware debugging skills.
Zoox
Foster City, CA
Develops operating-system platforms, device drivers, and infrastructure for autonomous-vehicle robotics systems. The role requires 4+ years of production software experience, strong Linux internals expertise, and proficiency in C/C++ plus scripting languages.
Motive
United StatesResearches and expands vehicle telematics coverage by analyzing automotive network traffic, OEM documentation, and field logs. The role requires hands-on vehicle interfacing, reverse engineering, programming, physical debugging tools, and automotive communication standards expertise.
Applied Intuition
Washington, DC
Designs and integrates C++ autonomy software with UAV hardware, autopilots, sensors, and communication systems, supporting SIL/HIL validation and live flight testing. Requires 3+ years of robotics integration experience, U.S. citizenship, and security-clearance eligibility.