NVIDIA is well positioned as the “AI Computing Company”, our GPUs being the brains that power modern Deep Learning software frameworks, accelerated analytics, modern data centers, and driving autonomous vehicles. We are looking for a Software QA Test Development Engineer Intern to join in the mission of crafting a distributed technology for all NVIDIA teams that remotely manage tens of thousands of resources in a simple and controlled fashion, allowing engineers to focus on engineering and automation, rather than being burdened by manual operational tasks.

What you'll be doing:

• Analyze requirements and design test matrices covering functionality, performance, robustness, and edge cases.
• Develop test plans and cases; build and maintain automated test suites (API / UI / CLI / E2E) in Python; enhance framework architecture and implementation.
• Leverage AI-powered tools and agentic workflows to accelerate case generation, triage, and root cause analysis.
• Integrate automation testing in CI/CD pipelines to build reliable fast feedback loops.
• Manage the full bug lifecycle — filing, reproduction, and driving multi-functional collaboration to resolution.
• Reproduce and verify customer-reported issues to ensure quality before release.
• Find opportunities to improve QA efficiency through tooling and automation.

What we need to see:

• Currently pursuing a MS or higher degree in CS/EE/CE or related field
• Solid software development skills with hands-on project experience.
• Proficient in Python; familiar with Unix/Linux and shell scripting.
• Experience using AI-powered development tools to boost productivity in real projects.
• Familiarity with Docker / Kubernetes and cloud-based test infrastructure.
• Familiarity with test methodologies — test design, automation, and defect analysis.
• Strong QA instinct — attention to detail, analytical, systematic problem-solver.
• Fluent English (written & spoken); takes initiative and collaborates well.
• Ability to work full-time, on-site five days per week, for one year.

Ways to stand out from the crowd:

• Hands-on with Agentic AI workflows — AI agents for task automation or intelligent testing.
• Built E2E test automation frameworks (pytest, CI/CD integration).
• Open-source contributions or visible GitHub portfolio.
• Knowledge of LLM evaluation — prompt engineering, accuracy measurement, or AI guardrails.
• Prior experience in a fast-paced, ship-focused environment.

Join our team of world-class engineers and be part of the groundbreaking work we do at NVIDIA. This internship offers an excellent opportunity to learn from experienced engineers, work on innovative technology, and make significant contributions. We are committed to fostering a collaborative and inclusive environment, where every team member has the opportunity to thrive and make a significant impact.