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XPENG · 3 weeks ago

Senior Staff Machine Learning Engineer - Foundation Model

Santa Clara, CA

Full-time

Onsite

Senior Level, Lead/Staff

$244K/yr - $413K/yr

3+ years exp

XPENG is a leading smart technology company focused on innovation in AI and autonomous driving. They are seeking a Machine Learning Engineer / Research Scientist to develop the Vision-Language-Action Foundation Model for autonomous driving systems, collaborating with researchers and engineers to design and deploy multi-modal models.

AutomotiveAutonomous VehiclesElectric VehicleManufacturing

Hiring Manager

Yuqing Wang, SHRM-CP

Responsibilities

Design and implement large-scale multi-modal architectures (e.g., vision–language–action transformers) for end-to-end autonomous driving

Develop pretraining and fine-tuning strategies leveraging massive labeled and unlabeled fleet data (images, video, LiDAR, CAN bus, maps, human driving behaviors, etc.)

Research and integrate cross-modal alignment (e.g., visual grounding, temporal reasoning, policy distillation, imitation and reinforcement learning) to improve model interpretability and action quality

Collaborate with infrastructure engineers to scale training across thousands of GPUs using distributed training frameworks (FSDP, DDP, etc.)

Conduct systematic ablation, evaluation, and visualization of model behavior across perception, reasoning, and planning tasks

Contribute to model deployment optimization , including quantization, export, and latency–accuracy trade-offs for onboard execution

Qualification

Deep learning researchPyTorchMulti-modal modelingDistributed trainingRepresentation learningCollaboration skillsProblem-solving skills

Required

Master's degree or higher in Computer Science, Electrical/Computer Engineering, or related field, with 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

Preferred

PhD in CS/CE/EE or 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 (e.g., ViT, Flamingo, BEVFormer, RT-2, or GRPO-style policies)

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

Competitive compensation package.

Snacks, lunches, dinners, and fun activities.

Company

XPENG

Glassdoor2.8

XPeng is a leading Chinese Smart EV company that designs, develops, manufactures, and markets Smart EVs that appeal to the large and growing base of technology-savvy middle-class consumers.

Founded in 2014

Guangzhou, Guangdong, CHN

10001+ employees