NVIDIA
SWQA Test Development Intern, GPU Communications Libraries - 2027
Skills
2 months ago
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Important information
Contract type:
Permanent
Location:
Shanghai, China
Work mode:
Onsite
Published on:
20 August 2026
What they need
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
What you’ll be doing:
- Be responsible for running test cases to validate NVIDIA GPU Communications Libraries (NCCL, NVSHMEM, UCX, GDRCopy, GPUDirect RDMA etc).
- Be responsible to automate test cases and maintain the automation scripts.
- Collaborate with Developer, PM, marketing, and engineering teams on crafting test plan and implementing validation.
What we need to see:
- Currently pursuing a MS or higher degree in CS/EE/CE
- Good experience using AI development tools to design and automate tests
- Experience with Linux OS
- Good at Shell/Python programming skills
- Fluent oral and written English
- Good QA sense, knowledge, and experience in software testing
- Great problem-solving skills with strong interpersonal skills, quick learner, proactive, innovative, and committed
- Strongly self-motivated with a passion to learn new hardcore technology
- Able to work 5 days every week with 12 months available
Ways to stand out from the crowd:
- Experience building AI-driven solutions that improve efficiency and enhance end-to-end QA workflows
- Experiences in C/C++ programming and debug skills
- Experience with CUDA programming and NVIDIA GPUs
- Knowledge of high-performance networks like InfiniBand, RoCE, etc
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