Director, Embodied AI & Edge Systems(J31965)

1. Develop world models and embodied control systems for vehicles and mobile robots to achieve environmental understanding and autonomous actions. 2. Build a high-fidelity simulation platform to support the training and validation of AI models in virtual environments. 3. Overcome the key technologies of AI Runtime on the edge side to achieve efficient and low-latency operation of large models on the vehicle end. 4. Promote underlying technologies such as compilation optimization, operator customization, and heterogeneous computing to enhance inference performance. 5. Explore the "vehicle-cloud" collaborative intelligent architecture to support the distributed execution and status synchronization of complex tasks.

Have a research and development background related to robot control, world models, simulation systems or edge computing. 2. Familiar with technology stacks such as ROS, Unity/Unreal simulation engines, SLAM, and motion planning. 3. Have experience in deploying AI models to embedded platforms (such as automotive-grade chips), and be proficient in model compression and inference optimization. 4. Have practical project experience in areas such as embodied intelligence, humanoid robots, and autonomous driving perception and decision-making. 5. Understand the interaction mechanism of "brain - body - environment", and possess the ability of cross-modal fusion and real-time control.