Deep Learning Software Engineering Intern, Test Development - 2027
About the role
What you’ll be doing
- GPU Software testing and test automation improvement for NVIDIA Deep Learning Software products, such as cuDNN, TensorRT, NVIDIA optimized Frameworks (E.g. TensorFlow, PyTorch, MxNET, etc.)
- Be responsible for functionality, compatibility, and performance tests in DL SW stack release.
- Work with development teams to triage issues, root cause analysis, verify fixes, define new tests, improve test plans.
- Utilize AI-powered tools to improve efficiency and quality, including test case/plan/script generation, defect detection, CBTP, bug fixing and day to day assistance.
What we need to see
- Pursuing MS or higher degree in CS/EE/CE.
- Scripting language (Python, Perl, bash), Linux knowledge is required.
- Experiences in C/C++ programming is a plus.
- Familiarity any Deep Learning Framework is a strong plus.
- Good communication skills, fluent oral and written English.
- Experience with AI tools.
Ways to stand out from the crowd
- Familiarity working with NVIDIA GPU hardware is a strong plus.
- Background with NVIDIA GPU Computing (CUDA) is a strong plus.
- Proven success in leveraging AI tools to significantly improve efficiency, streamline workflows or enhance process automation.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Not included in the source posting: about the role, qualifications, benefits.
Skills
Who can apply
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