Software QA Engineer - AI Data Centers

We are seeking a motivated QA Engineer to join NVIDIA’s Data Center Networking. In this role, you will help validate next-generation data center platforms that power AI, cloud, and high-performance computing. You will be part of a team ensuring our firmware, drivers, and networking solutions meet industry-leading standards of efficiency and quality. This is a hands-on opportunity to work with advanced hardware, large-scale environments, and cutting-edge technologies, while gaining real-world QA and automation experience.

What you'll be doing:

Design, develop, and execute test plans for firmware and driver releases.

Perform manual and automated testing across regression, performance, scalability, and security domains.

Build and maintain test topologies in large-scale data center and AI-driven environments.

Develop and extend Python-based automation frameworks to improve coverage and efficiency.

Identify, reproduce, and track issues; collaborate with R&D to drive analysis and validate fixes.

What we need to see:

B.Sc. degree in Computer Science, Electrical/Computer Engineering

1+ years of Knowledge at Networking protocols and Linux systems.

Programming / scripting skills (Python preferred).

Good communication skills and the ability to work effectively in a team.

Strong motivation to learn and grow in firmware, networking, data center, and AI-related QA.

Ways to stand out from the crowd:

Previous or hands-on experience in QA or networking validation.

Experience with data center networking, AI workloads, virtualization, or cloud platforms.

Proactive, curious, and eager to take ownership of technical challenges.

At NVIDIA, you will work side-by-side with some of the best engineers in the industry, gaining mentorship, training, and hands-on experience that will accelerate your career. You’ll be exposed to state-of-the-art data center and AI technologies that drive the world’s most advanced applications. This role offers the chance to contribute to real product validation while building the skills, network, and knowledge to grow into a future leader in QA, firmware, networking, and AI-driven data center engineering.