Networking QA and Automation Engineer, Network Systems

Overview

• NVIDIA is looking for a Software QA Engineer with a strong background in Networking and Automation to join our InfiniBand (IB) and NVLINK (NVL) Switch QA team.
• Our team is responsible for qualifying software stack for NVIDIA’s IB Switch, Router, Gateway and NVLINK systems, delivering world-class networking solutions.
• You will work at the heart of cutting-edge technology, validating software management features, designing topologies, developing automated test suites, and collaborating with engineering and product teams to ensure delivery of robust and scalable systems.
• What you’ll be doing: Design, develop, and execute manual and automated tests as part of software stack releases.
• Define, build, and manage testbed topologies for functional, regression, and performance validation.
• Analyze architectural designs and feature requirements for new networking capabilities.
• Debug failures, identify root causes, and verify fixes delivered by development teams.
• Schedule test runs, track testing progress, and generate test status reports with detailed defect documentation.
• Write and maintain automation tests across multiple frameworks (Python, Perl), enhancing test efficiency and scalability.
• Collaborate with cross-functional global teams including R&D, product marketing, and system verification.
• What we need to see: B.Sc.
• in Computer Science, Information Systems, Electrical Engineering, or related technical field.
• 1-3 years of hands-on experience in the field of QA testing Strong understanding of software testing methodologies, test planning, and bug lifecycle.
• Hands-on experience in automation scripting (Python, Perl, or Shell) on Unix/Linux platforms.
• Familiarity with networking concepts, protocols, and devices (e.g., switches, NICs).
• Strong analytical and debugging skills with an eye for detail.
• Clear verbal, proficient written and spoken English Ways to stand out from the crowd: Experience in Python automation and working with source control tools (Git, Gerrit), Solid knowledge of Linux and kernel internals.
• Hands-on experience with virtualized and mixed computing environments (KVM, VMware, Linux/Windows).
• Experience using Generative AI platforms / LLMs such as Gemini, Claude, Copilot, etc.
• to develop tools powered by artificial intelligence.
• In-depth understanding of TCP/IP, routing protocols, LAN switching, and data center topologies.
• Exposure to QA methodologies, release management, and end-to-end test lifecycle.
• Familiarity with NVIDIA technologies such as Infiniband, NVLINK, GPUs is a strong advantage.