INTERNSHIP DETAILS

AI Intern – VLA Deployment

CompanyXPENG
LocationSanta Clara
Work ModeOn Site
PostedMay 5, 2026
Internship Information
Core Responsibilities
Support the optimization and deployment of large-scale multimodal and VLA models onto vehicle-grade compute platforms. Contribute to deployment tools, test pipelines, and performance tuning to ensure real-time production readiness.
Internship Type
full time
Company Size
2304
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
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. Its mission is to drive Smart EV transformation with technology and data, shaping the mobility experience of the future. In order to optimize its customers’ mobility experience, XPeng develops in-house its full-stack advanced driver-assistance system technology and in-car intelligent operating system, as well as core vehicle systems including powertrain and the electrical/electronic architecture. XPeng is headquartered in Guangzhou, China. In 2021, the Company established its European headquarters in Amsterdam, along with other dedicated offices in Copenhagen, Munich, Oslo, and Stockholm.The Company’s Smart EVs are mainly manufactured at its plant in Zhaoqing and Guangzhou，Guangdong province. For more information, please visit https://www.xpeng.com/
About the Role
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.
 
The Mission: Vision-Language-Action (VLA) models and foundation models are becoming increasingly important in autonomous driving, but turning research models into real-time, production-ready systems on vehicle hardware remains a major challenge. We are looking for an entry-level engineer or intern to support the optimization and deployment of multimodal models onto vehicle-grade compute platforms. This role is a strong fit for candidates who are excited about deep learning systems, model deployment, and edge inference for real-world autonomous driving applications.

Key Responsibilities

  • Support model quantization and deployment efforts for large-scale multimodal models, including Transformers and vision-language models.
  • Assist with applying model optimization techniques such as post-training quantization, quantization-aware training, pruning, and related compression methods under guidance from senior engineers.
  • Work with research and platform teams to help improve model deployability and understand hardware and runtime constraints.
  • Contribute to deployment tools, test pipelines, and runtime modules in C++ and Python for autonomous driving systems.
  • Help analyze model performance, memory usage, latency, and numerical accuracy across different deployment targets.
  • Participate in debugging and performance tuning across the model, runtime, and system stack.
  • Support validation and testing workflows to ensure stable and reliable deployment in vehicle and simulation environments.

Basic Qualifications

  • BS, MS, or PhD in Computer Science, Electrical Engineering, Robotics, or a related field.
  • Strong programming skills in C++ and/or Python.
  • Familiarity with deep learning frameworks such as PyTorch.
  • Basic understanding of model inference, deployment, or optimization workflows using tools such as ONNX, TensorRT, or similar frameworks.
  • Exposure to model compression or quantization concepts such as INT8, FP16, or related approaches.
  • Interest in computer architecture, performance optimization, and edge or embedded systems.
  • Strong problem-solving skills and the ability to learn quickly in a fast-paced engineering environment.
  • Good communication skills and the ability to collaborate with cross-functional teams.

Preferred Qualifications

  • Internship, research, or project experience in deep learning model deployment, inference acceleration, or embedded AI.
  • Familiarity with Transformers, multimodal models, or foundation models.
  • Experience with CUDA or GPU programming.
  • Exposure to autonomous driving, robotics, or real-time systems.
  • Contributions to research projects, open-source repositories, or relevant course projects.
What do we provide:
  • A fun, supportive and engaging environment.
  • Infrastructures and computational resources to support your work.
  • Opportunity to work on cutting edge technologies with the top talents in the field.
  • 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.
 
We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.
Key Skills
C++PythonPyTorchONNXTensorRTModel QuantizationModel PruningCUDAGPU ProgrammingDeep LearningModel DeploymentEdge InferenceTransformersMultimodal ModelsComputer ArchitectureEmbedded Systems
Categories
TechnologyEngineeringSoftwareScience & ResearchTransportation
Benefits
Supportive EnvironmentComputational ResourcesCompetitive Compensation PackageSnacksLunchesDinnersFun Activities