Staff Machine Learning Engineer

• Develop and improve 2D traffic sign detection models for autonomous driving perception systems.
• Analyze TSR-related scenarios and failure cases, and prepare/curate training datasets.
• Design and execute model training experiments, optimize models for production deployment (ONNX/TensorRT/quantization).
• Build and maintain evaluation pipelines, collaborate with cross-functional teams to improve detection performance.

This role directly improves traffic sign recognition for autonomous driving systems, enhancing driving safety, rule understanding, and product quality, contributing to the future of intelligent mobility and transportation revolution.

• Master’s or PhD in Computer Science, Electrical Engineering, Robotics, Computer Vision, Machine Learning, or related field.
• 3-5 years hands-on experience with computer vision models, especially object detection (YOLO, Faster R-CNN, DETR, etc.).
• Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
• Experience with detection metrics (mAP, precision/recall, false positive/negative analysis) and model debugging.

Competitive compensation package including base salary range $215,280 - $364,320 (USD), plus bonus, equity, and benefits. Snacks, lunches, dinners, and fun activities. Opportunity to work on cutting-edge technologies with top talents.

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into electric vehicles, eVTOL aircraft, and robotics, dedicated to reshaping the future of transportation.