Software Engineer Intern

4 weeks ago

Shanghai, Shanghai, China NVIDIA Full time
Join Our Team of Innovators

NVIDIA is a leader in the field of artificial intelligence and autonomous vehicles. We are seeking a highly motivated and talented Software Engineer Intern to join our team and contribute to the development of our autonomous vehicle platform.

About the Role

  • Design and implement software platforms for autonomous vehicles, including application design, kernel modifications, driver implementation, system integration, performance optimization, and stress/stability testing.
  • Integrate the full-stack software, including system software, AV application, DNN, and kernel, to build a start-of-the-art autonomous vehicle platform.
  • Drive the reliability of the software platform, which includes time synchronization, vehicle network, RADAR, LiDAR, camera sensor processing, and fusion.
  • Develop and maintain large language model (LLM) based applications to serve the AV platform, such as LLM based QA bots and debug tips.
  • Based on the industry's most advanced technology, develop massive data processing from autonomous driving.
  • Triage automotive vehicle fleet issues and debug with the global team.
  • Work in an environment that involves Linux and QNX RTOS.

Requirements

  • Pursuing a BS or MS in CS/CE/EE or equivalent program.
  • Experience in research and development of Deep Learning/Transformer/NLP/LLM technology.
  • Excellent programming skills in some rapid prototyping environment such as Python/C/C++.
  • Strong Linux kernel, application-level system software experience.
  • Ability and flexibility to work and communicate effectively in a multinational, multi-time-zone corporate environment.
  • Self-motivated and a good teammate.

What We're Looking For

  • Prior experience in the automotive field.
  • Background in QNX RTOS and debug tools. Worked with CAN and tools, RADAR, LiDAR.
  • Gather knowhow on datasets for LLM training & evaluation.
  • Experience in developing and maintaining AI or machine learning infrastructure, preferably in the context of large language models.

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