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XPENG · 1 day 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 at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles. They are seeking a Senior Staff Machine Learning Engineer to drive the modeling and algorithmic development of their next-generation Vision-Language-Action Foundation Model, which powers their autonomous driving systems.

AutomotiveAutonomous VehiclesElectric VehicleManufacturing

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 modelingTransformer-based model designDistributed trainingRepresentation learningCollaboration skillsProblem-solving skillsCommunication 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

A collaborative, research-driven environment with access to massive real-world data and industry-scale compute.

An opportunity to work with top-tier researchers and engineers advancing the frontier of foundation models for autonomous driving.

Direct impact on the next generation of intelligent mobility systems.

Opportunity to make significant impact on the transportation revolution by the means of advancing autonomous driving.

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