运动控制算法资深专家（具身智能）-火山引擎
Core
Lead R&D of whole-body control algorithms for humanoid embodied robots, including architecture design, reinforcement learning (RL) motion control models, and Whole-Body Control (WBC).
Role type
Senior IC machine-learning engineer (robotics/embodied AI)
Builds
Whole-body control systems for humanoid robots
Domain
Robotics, Embodied AI, Reinforcement Learning
Deliverable
production ML models
Required skills
Reinforcement learning (PPO, SAC), Whole-Body Control (WBC), Model Predictive Control (MPC), Sim2Real transfer, C++, Python, ROS/ROS2, Robot kinematics/dynamics modeling
Preferred skills
Team management, System-level architecture design, Embedded system optimization
Responsibilities
Design and develop RL-based whole-body control architectures; Build and maintain RL training, evaluation, and deployment pipelines; Integrate algorithms into simulation and hardware for system validation; Optimize control performance for embedded systems; Lead technical reviews and drive project delivery with internal/external teams.
Seniority
Senior, hands-on IC with leadership responsibilities
