Deep Learning Software Engineering Intern, Test Development - 2027
Before you apply
Listed location: China, Shanghai
Work arrangement: onsite. A remote label does not confirm worldwide eligibility or visa sponsorship.
Read the employer’s description for qualifications, compensation and work eligibility. Confirm the position is still open on the application page.
Job description supplied by NVIDIA; category and skill labels may be inferred. How our listings work · Report a problem
Job Description
We are now looking for a Deep Learning Software Test Development Engineer Intern!
The position is in NVIDIA Deep Learning Software Quality Assurance team that defines, develops and performs tests to validate robustness and measure the performance of NVIDIA‘s Deep Learning software and GPU Infrastructure for autonomous driving, healthcare, speech recognition, natural language processing, and a wide variety of other AI scenarios. This team collaborates with multiple AI product teams to develop new products; derive and improve complex test plans; and improve our workflow processes for a diverse range of GPU computing platforms. You should grow with being in the critical path supporting developers working for billion-dollar business lines as well as intimately understanding the values of responsiveness, thoroughness and teamwork. You should constantly foster and implement efficiency improvements across your domain. Join the team which is building software which will be used by the entire world!
What you’ll be doing:
Be responsible for functionality, compatibility, and performance tests in NVIDIA AI SW stack release.
Develop, maintain, and improve test automation infrastructure with using AI tools. Use AI to improve quality and productivity across QA End-to-End workflow.
Work with development teams to triage issues, root cause analysis, verify fixes, define new tests, improve test plans.
What we need to see:
Pursuing MS or higher degree in CS/EE/CE or a related field.
Proven success in leveraging AI tools to significantly improve efficiency, streamline workflows or enhance process automation.
Good python, C++ programming skillset, Linux knowledge is required.
Experience in software development with popular AI models is a strong plus.
Good communication skills, fluent oral and written English.
Ways to stand out from the crowd:
Be familiar with deep neural network training, inference, optimization in typical DL Frameworks.
Background with NVIDIA GPU Computing (CUDA) is a strong plus.
With highly competitive salaries and a comprehensive benefits package, 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 want to hear from you. Come, join our AI Software QA Test development team, and help build the real-time, cost-effective computing platform driving our success in the exciting and quickly growing field of AI.
#deeplearningSkills mentioned
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Frequently asked questions
Is the Deep Learning Software Engineering Intern, Test Development - 2027 position at NVIDIA remote?
The Deep Learning Software Engineering Intern, Test Development - 2027 role at NVIDIA does not have a confirmed remote arrangement in our data. Check the employer description for its work location.
What type of employment is the Deep Learning Software Engineering Intern, Test Development - 2027 role?
NVIDIA is hiring for a full-time Deep Learning Software Engineering Intern, Test Development - 2027 position.
Which skills are mentioned for the Deep Learning Software Engineering Intern, Test Development - 2027 job at NVIDIA?
Detected skill labels include Python, CUDA, GPU. Check the employer description to distinguish required skills from preferred experience.
How do I apply for the Deep Learning Software Engineering Intern, Test Development - 2027 position at NVIDIA?
You can apply for the Deep Learning Software Engineering Intern, Test Development - 2027 role directly through NVIDIA's official application link provided on this page.
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