About the job
We are seeking a Robotics/AI Motor Control Scientist to develop cutting-edge machine learning algorithms for motor control systems in robots. In this role, you will focus on creating and optimizing intelligent motor control strategies to enable robots to perform complex, whole-body tasks. Your contributions will be essential in advancing robotics by enabling fluid, reliable, and safe interactions between robots and their environments.
Responsibilities
Develop controllers that leverage reinforcement learning, imitation learning, or other advanced AI techniques to achieve natural, robust, and adaptive motor behaviors
Collaborate with multi-disciplinary teams to integrate motor control systems with robotic hardware, ensuring alignment with real-world constraints such as actuator dynamics and energy efficiency
Use simulation and real-world testing to refine and validate control algorithms
Stay updated on advancements in robotics, AI, and control systems to apply advanced techniques to robotic motion challenges
Lead technical projects from conception through production deployment
Mentor junior scientists and engineers
Bridge research initiatives with practical engineering implementation
Qualifications
Minimum
PhD, or Master's degree and 6+ years of applied research experience
3+ years of industry or academic research experience
Experience in Java, C++, Python, or a related language
Experience leading technical initiatives and key deliverables
Experience in mentoring, leading, or managing more junior engineers
Strong publication record at major Robotics/ML/AI conferences (e.g., RSS, CoRL, ICRA, IROS, NeurIPS, ICML, ICLR)
Experience with simulation environments for robot learning (Isaac Gym/Lab, MuJoCo, or similar)
Experience with sim-to-real transfer for robotic systems
Strong understanding of kinematics and motion planning for robotic systems
Experience with reinforcement learning, imitation learning, or other AI techniques applied to robotic motor control
Preferred
Experience working with PyTorch or JAX software, or experience programming with at least one software programming language
History of impactful first-author publications at major conferences
Experience with large-scale distributed training for RL
History of technical leadership and cross-functional collaboration
Experience bridging research with practical engineering implementation in robotics systems
Experience bridging academic research and production robotics
Experience integrating perception systems (e.g., vision and touch sensors) into motor control pipelines
Familiarity with hardware constraints and actuator dynamics for robots