NVIDIA

Software QA Engineer Intern - 2025

Shanghai, China
Deep Learning Shell Python Docker Kubernetes
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Description

NVIDIA is the world leader in GPU Computing. We are passionate about markets include gaming, automotive, professional vision, HPC, datacenters and networking in addition to our traditional OEM business. NVIDIA is also well positioned as the ‘AI Computing Company’, and NVIDIA GPUs are the brains powering modern Deep Learning software frameworks, accelerated analytics, modern data centers, and driving autonomous vehicles. We have some of the most experienced and dedicated people in the world working for us. If you are dedicated, forward-thinking, and if working with hard-working technical people across countries sounds exciting, this job is for you.

We are now looking for a Software QA Test Development Engineer Intern, you will collaborate with multi-functional groups. SWQA test developer engineer at NVIDIA is responsible for test planning, execution, and reporting, you will also write scripts to automate testing, design and develop tools for QA team, or develop integration tests for validation, so QA engineer can improve productivity or optimize test plan. As a SWQA test developer, you must identify weak spots and constantly design better and creative test plans to break software and identify potential issues. You will have a huge impact on the quality of NVIDIA's products.

What you’ll be doing:

  • Be responsible for executing test cases to validate NVIDIA enterprise offerings, such as NIM.

  • Automate test cases and maintain the automation scripts.

  • Work with development teams to triage issues, root cause analysis, verify fixes, define new tests, and improve test plans.

What we need to see:

  • Currently pursuing a BS or higher degree in CS/EE/CE.

  • Fluent oral and written English.

  • Comfortable working with Linux OS.

  • Good at shell/python programming skills.

  • Good QA sense, knowledge, and experience in software testing.

  • Great problem-solving skills.

  • Good interpersonal skills, quick learner, proactive, innovative, and committed.

  • Strongly self-motivated with a passion to learn new hardcore technology.

  • Able to work 4 days every week with at least 6 months available.

Ways to stand out from the crowd:

  • Experience working with NVIDIA GPU hardware is a strong plus.

  • Background in parallel programming ideally is a plus.

  • Experience with virtualization technologies like Docker, Kubernetes, OpenStack.

NVIDIA
NVIDIA
Artificial Intelligence (AI) GPU Hardware Software Virtual Reality

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