Responsible for the deployment, optimization, and verification of deep learning perception models on vehicle-side embedded platforms
Job Summary
Responsible for the deployment, optimization, and verification of deep learning perception models on vehicle-side embedded platforms.
Engage in system-level engineering work in a Linux Embedded environment, including driver and system configuration collaboration.
Collaborate closely with algorithm, fusion, system, and hardware teams to achieve stable integration and long-term evolution of perception modules within the vehicle system.
Matching Summary
Responsible for the deployment, optimization, and verification of deep learning perception models on vehicle-side embedded platforms.
Skills & Requirements
Must-have
Deep learning model deployment
Embedded platform optimization
Jetson / Orin platforms
TensorRT, CUDA, cuDNN, ONNX Runtime
Linux Embedded system engineering
C++ and Python programming
LiDAR point cloud experience
Nice-to-have
Multithreaded parallel processing
CUDA acceleration experience
Object detection/segmentation understanding
ROS2, DeepStream framework knowledge
System stability and maintainability focus
Key Requirements
Bachelor's degree or higher
Computer, Automation, Electrical Engineering, AI, or related major