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NVIDIA • Shanghai, Shanghai, China
Role & seniority: Graduate QA Engineer / QA Intern (Masters student; full-time, up to 1 year)
Stack/tools: Python, shell scripting; Linux OS; AI development tools for QA workflow; test plan creation, test case development, test automation; virtualization tech (nice-to-have: Docker, Kubernetes, OpenStack)
Execute test cases to validate NVIDIA GPU Cloud products
Automate test cases and maintain automation scripts
Collaborate with development teams to triage issues, perform root cause analysis, verify fixes, define new tests, and improve test plans
Currently pursuing Master’s degree in Computer Science or Electronic Engineering
Fluent in English (oral and written)
Experience using AI development tools to improve QA workflow (planning, case development, automation)
Proficient in Python and shell scripting
Good knowledge of Linux OS
QA/testing experience and strong problem-solving skills
Interpersonal skills, quick learner, proactive, self-motivated, committed
Ability to work full-time up to 1 year
Experience with NVIDIA GPU hardware
Background in parallel programming
Experience with virtualization technologies (Docker, Kubernetes, OpenStack)
Location & work type: Location not specified; Full-time position up to 1 year
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 executing test cases to validate NVIDIA GPU Cloud products Automate test cases and maintain the automation scripts Work with development teams to triage issues, root cause analysis, verify fixes, define new tests, improve test plans
What We Need To See
Currently pursuing Master's degrees in Computer Science and Electronic Engineering Fluent oral and written English Experience in using AI development tools to improve quality and productivity across the end-to-end QA workflow, including test plan creation, test case development, and test automation Proficient in Python and shell scripting Good Knowledge on Linux OS 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 full time up to 1 year
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
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