Software Engineering Intern, Test Development - 2027

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:
Test NVIDIA AI agents and end-to-end agentic workflows across NV GPU Platform.
Design and execute functional, integration, end-to-end, reliability, and performance tests.
Develop automated tests and evaluation frameworks for capabilities such as reasoning, tool use, multi-turn interactions, memory, and retrieval.
Use AI development tools to improve productivity across test planning, test case development, execution, analysis, and automation.
Collaborate with development teams to triage issues, perform root-cause analysis, verify fixes, and improve test coverage and quality.
What we need to see:
Currently pursuing a master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
Strong software development potential, with proficiency in Python and shell scripting.
Familiarity with AI, machine learning, large language models, or AI agent technologies.
Experience using AI development tools to improve quality and productivity across the end-to-end QA workflow.
Good knowledge of Linux and software testing methodologies.
Strong problem-solving, communication, and interpersonal skills.
Fluent written and spoken English.
A proactive, innovative, and self-motivated attitude with a passion for learning cutting-edge technologies.
Ability to work full-time, on-site five days per week, for one year.
Ways to stand out from the crowd:
Background with testing LLM applications, AI agents, or agentic workflows.
Experience developing AI evaluation or test automation frameworks.
Knowledge of RAG, tool calling, prompt engineering, or multi-agent systems.
Background with Docker, Kubernetes, OpenStack, or other cloud-native technologies.
Experience with NVIDIA GPU hardware, CUDA, or parallel programming.