XPENG
AI & Machine LearningDirect Greenhouse career site

Staff Machine Learning Engineer - Foundation Model

Pay
$215,280 – $364,320 per year
Location
Santa Clara, CA · On-site
Job type
Full-time
Level
Lead / Staff
Experience
3+ years
Education
Master's degree
Listed
30 days ago

Skills & highlights for this role

  • PyTorch
  • transformer architectures
  • distributed training (DDP, FSDP)
  • self-supervised learning

Also useful

  • RLHF/DPO/GRPO
  • BEVFormer
  • large-batch optimization

Stated benefits & perks

  • Bonus
  • Equity

Key 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.

Minimum Qualifications

  • 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 Qualifications

  • 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.

What do we provide

  • 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.

Pay and benefits

The base salary range for this full-time position is $215,280-$364,320, in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

About XPENG

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.

We are looking for a full-time Machine Learning Engineer / Research Scientist to drive the modeling and algorithmic development of XPENG's next-generation Vision-Language-Action (VLA) Foundation Model - the core brain that powers our end-to-end autonomous driving systems.

You will work closely with world-class researchers, perception and planning engineers, and infrastructure experts to design, train, and deploy large-scale multi-modal models that unify vision, language, and control. Your work will directly shape the intelligence that enables XPENG's future L3/L4 autonomous driving products.

Read the original posting

From XPENG's careers page, first listed on Rolev.ai on October 10, 2026. Rolev.ai is not the employer.

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Common questions

What is the salary for the Staff Machine Learning Engineer - Foundation Model role at XPENG?

The Staff Machine Learning Engineer - Foundation Model posting at XPENG states compensation of $215,280 – $364,320 per year. It is listed as a full-time position. Final pay may depend on location, experience, and interview evaluation on XPENG's official career site.

Where is the Staff Machine Learning Engineer - Foundation Model job at XPENG located?

This Staff Machine Learning Engineer - Foundation Model position at XPENG is located in Santa Clara, CA (On-site). Always check XPENG's application page for specific state eligibility or relocation policies.

What qualifications are required for Staff Machine Learning Engineer - Foundation Model at XPENG?

For the Staff Machine Learning Engineer - Foundation Model role, XPENG highlights 3+ years of relevant experience; a master's degree; experience with PyTorch, transformer architectures, distributed training (DDP, FSDP), self-supervised learning. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.

How do I apply for the Staff Machine Learning Engineer - Foundation Model position at XPENG?

This listing links directly to XPENG's Greenhouse application page. You can apply directly on XPENG's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Greenhouse application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.