Student Veterans of America Jobs

Welcome to SVA’s jobs portal, your one-stop shop for finding the most up to date source of employment opportunities. We have partnered with the National Labor Exchange to provide you this information. You may be looking for part-time employment to supplement your income while you are in school. You might be looking for an internship to add experience to your resume. And you may be completing your training ready to start a new career. This site has all of those types of jobs.

Here are a few things you should know:
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  • Jobs on this site are original and unduplicated and come from three sources: the Federal government, state workforce agency job banks, and corporate career websites. All jobs are vetted to ensure there are no scams, training schemes, or phishing.
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  • The newest jobs are listed first, so use the search features to match your interests. You can look for jobs in a specific geographical location, by title or keyword, or you can use the military crosswalk. You may want to do something different from your military career, but you undoubtedly have skills from that occupation that match to a civilian job.
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Nvidia System Software Engineer Intern - Autonomous Vehicles Platform in Shanghai, China

The Autonomous Vehicles Platform team is searching for engineers to develop and bring NVIDIA's automotive platform out to the world. You will participate in a focused effort to develop and productize ground-breaking solutions that will redefine the world of transportation and the growing field of self-driving cars. Work with hardworking and dedicated multi-functional engineering development teams across various vehicle subsystems to integrate their work into our autonomous driving DRIVE SW platform, while achieving or exceeding all meaningful NVIDIA and automotive standards & guidelines. You'll find the work is exciting, fun, and very meaningful. We have customers and competition.

NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can pursue, and that matter to the world. This is our life’s work: to amplify human creativity and intelligence. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. If you're creative, autonomous, and love a challenge, we would love to hear.

What you'll be doing:

  • Design and implement Automotive Vehicles software platforms, including application design, kernel modifications/extensions, driver implementation/enhancement, system integration, performance optimization, stress/stability & tools development

  • Integrate the full-stack software including system software, AV application, DNN, and kernel together to build the start-of-art Automotive Vehicle platforms

  • Drive the reliability of the software platform, which includes Time sync, Vehicle Network, RADAR, LiDAR, Camera sensor processing, and fusion

  • Develop and maintain LLM based applications to serve AV platform, such as LLM based QA bot, debug tips etc.

  • Based on the industry's most advanced technology, develop the massive data processing from autonomous driving

  • Triage the Automotive Vehicle Fleet issues and debug with the global team

  • Work in an environment that involves Linux & QNX RTOS

    What we need to see:

  • Pursuing 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

    Ways to stand out from the crowd:

  • 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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