Staff Machine Learning Engineer - Foundation Model

The role

You will design, train and deploy large multi-modal models that combine vision, language and control. These models form the core intelligence for XPENG's end-to-end autonomous driving systems. You will work with researchers, perception and planning engineers, and infrastructure experts.

What you will do

• Design and implement large-scale multi-modal architectures for end-to-end autonomous driving.
• Develop pretraining and fine-tuning strategies using large fleet data (images, video, LiDAR, CAN bus, maps, human driving behaviors).
• Research cross-modal alignment, such as visual grounding, temporal reasoning, policy distillation, imitation and reinforcement learning.
• Work with infrastructure engineers to scale training across thousands of GPUs using distributed training frameworks.
• Run systematic ablation, evaluation and visualization of model behavior across perception, reasoning and planning tasks.
• Contribute to deployment optimization, including quantization, export and latency-accuracy trade-offs for onboard execution.

Required qualifications

• Master's degree or higher in Computer Science, Electrical/Computer Engineering, or a related field.
• 3+ years of experience in deep learning research or productization.
• Strong proficiency in PyTorch and modern transformer-based model design.
• Experience in large-scale pretraining or multi-modal modeling (vision, language, or planning).
• Deep understanding of representation learning, temporal modeling, and self-supervised or reinforcement learning techniques.
• Familiarity with distributed training (DDP, FSDP) and large-batch optimization.

Nice to have

• PhD in CS, CE, EE or a related field, with 1+ years of relevant industry experience.
• Publication record in top-tier AI conferences (CVPR, ICCV, NeurIPS, ICLR, ICML, ECCV).
• Prior experience building foundation or end-to-end driving models, or LLM/VLM architectures.
• Familiarity with RLHF/DPO/GRPO, trajectory prediction, or policy learning for control tasks.
• Proven ability to collaborate cross-functionally with infra, perception and planning teams to deliver production-ready models.

Benefits

• A collaborative, research-driven environment with access to large real-world data and industry-scale compute.
• Opportunity to work with top-tier researchers and engineers on foundation models for autonomous driving.
• Direct impact on the next generation of intelligent mobility systems.
• Competitive compensation package.
• Snacks, lunches, dinners and fun activities.
• Bonus, equity and benefits in addition to base salary.

Before you apply

• The salary range shown applies to all US locations.

About the company

XPENG is a smart technology company integrating AI and autonomous driving into electric vehicles, eVTOL aircraft and robotics. It focuses on intelligent mobility and cutting-edge R&D in AI and machine learning.