Design and implement deep learning algorithms for autonomous driving, optimizing neural networks for real-time performance, and integrating multimodal data.

The Data Infrastructure Engineer will analyze large datasets for edge cases in autonomous driving, collaborating with Machine Learning Engineers to improve safety and comfort.

Develop and optimize computer vision systems and multi-modal models, ensuring performance and efficiency, while collaborating with cross-functional teams.

Fine-tune and optimize LLMs (including multi-modal) for humanoid robots and autonomous vehicles; build scalable training and deployment pipelines; work on model efficiency (quantization, weight sharing), synthetic data generation, and cross-team product alignment.

Develop and maintain machine learning models for robotics applications, collaborate across teams, and contribute to innovative solutions in AI and mobility.

The Staff Technical Program Manager will coordinate software development for XPENG’s AI-driven vehicles, optimize agile practices, and manage program risks while tracking KPIs and OKRs.

The role involves developing and maintaining machine learning models for robotics, creating training and deployment pipelines, and collaborating on product needs.

You will build scalable data pipelines for processing large datasets, optimize training throughput, and evolve data storage solutions at XPENG.

Design and implement software modules for autonomous systems, optimize performance, and provide architectural guidance for other teams.

This role involves developing deep learning algorithms for autonomous driving, optimizing neural networks, and leveraging multimodal datasets for reinforcement learning and decision-making.