Deep Learning Software Engineering Intern, Test Development - 2027

We are now looking for a Deep Learning Software Test Development Engineering 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.

Responsibilities:

• GPU Software testing and test automation improvement for NVIDIA Deep Learning Software products, such as Edge-LLM, 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.

Requirements:

• 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 with any Deep Learning Framework is a strong plus.
• Good communication skills, fluent oral and written English.
• Experience with AI tools.

Preferred Qualifications:

• 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.