SonicJobs Logo
Left arrow iconBack to search

AI Infra Onboard Performance Intern

XPENG
Posted 3 months ago, valid for 10 days
Location

Santa Clara, CA 95052, US

Salary

Competitive

Contract type

Full Time

By applying, a XPENG account will be created for you. XPENG's Privacy Policy and Terms & Conditions will apply.

SonicJobs' Terms & Conditions and Privacy Policy also apply.

Sonic Summary

info
  • XPENG is a leading smart technology company focused on integrating advanced AI and autonomous driving technologies into vehicles, including electric vehicles and robotics.
  • The role involves designing and optimizing software for large-scale AI models, improving performance across various systems, and ensuring reliable optimizations for production vehicles.
  • Candidates should have a Master's or PhD in CS/CE/EE or equivalent, with at least 3 years of relevant industry experience and strong expertise in C++ and Python.
  • Preferred qualifications include experience with CPU or CUDA kernels, performance tooling, and familiarity with automotive compute platforms.
  • The position offers a competitive compensation package, a supportive work environment, and the chance to contribute to the future of transportation.
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.
 
 

Key Responsibilities

  • Design and optimize software for deploying large-scale AI models in production vehicles.
  • Profile and improve inference performance across compute, memory, and I/O systems.
  • Reduce latency and improve power efficiency on embedded automotive platforms.
  • Deliver production-ready optimizations that scale reliably across the vehicle fleet.

Basic Qualifications

  • Master's or PhD in CS/CE/EE or equivalent, with relevant industry or research experience.
  • Strong expertise in C++ and Python, including performance-sensitive, production-quality code.
  • In-depth understanding of computer architecture and high-performance computing (memory hierarchy, parallelism, vectorization, scheduling).
  • Proven experience in application performance analysis and optimization, using profiling tools to diagnose and resolve bottlenecks.

Preferred Qualifications

  • Experience writing and optimizing CPU or CUDA kernels.
  • Experience developing performance tooling and instrumentation (e.g., eBPF, perf, custom tracing/profiling frameworks) for production or embedded systems.
  • Familiarity with embedded or automotive compute platforms (e.g., NVIDIA Orin, Drive) and their power/thermal constraints.
  • Previous experience in the autonomous driving or robotics industry.
  • Effective at solving complex problems collaboratively within larger cross-functional teams.
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.



Learn more about this Employer on their Career Site

Apply now in a few quick clicks

By applying, a XPENG account will be created for you. XPENG's Privacy Policy and Terms & Conditions will apply.

SonicJobs' Terms & Conditions and Privacy Policy also apply.