Staff Machine Learning Engineer – Autonomous Driving Model Quantization & Deployment

Job description

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing ( eVTOL ) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning , and smart connectivity. The Mission: The challenge of Vision-Language-Action (VLA) models and Foundation Models isn't just their intelligence—it's their real-time execution at the edge . We are seeking a high-caliber Staff Machine Learning Engineer to bridge the gap between massive research models and production-ready L4 autonomous driving systems. You will lead the effort to optimize and deploy our VLA models onto vehicle-grade compute platforms for our global fleet. Key Responsibilities: Lead Optimization Strategy: Own the end-to-end quantization and optimization roadmap for large-scale multimodal models (Transformers, VLMs). Model Compression: Apply and innovate in PTQ (Post-Training Quantization), QAT (Quantization-Aware Training), and pruning techniques to fit VLA...