Senior QA Automation Engineer
NVIDIA
Senior QA Automation Engineer
NVIDIA
Designs the chips and software that power AI
What if your Python automation caught a critical ASIC bug before the physical silicon was even manufactured? At NVIDIA, our simulation platforms make that happen every release cycle! We are the System Ethernet QA Team at NVIDIA's R&D center, responsible for the testing and qualification of virtual networking silicon (SimX) and software—from L2 forwarding and L3 routing to overlays, QoS, and security. With SimX, developers and QA engineers get hardware-free, early access to the ASIC for better debugging.
We are looking for a Senior QA Software Engineer who combines network protocol expertise with strong Python automation skills. Does debugging a BGP EVPN route leak excite you as much as refactoring a test framework? Then we should talk!
What you'll be doing:
We don't just complete checklists; we collaborate closely with R&D to lead the quality of new features from design to deployment. In this role, we:
Review architectural designs and requirements for new features introduced to the product
Drive the design, development, and execution of tests across functional, performance, and security scopes as part of SW GA and update releases
Develop Python automation suites built on clean OOP principles
Chase down defects and validate fixes until we fully resolve the root cause
Leverage the SimX platform to validate code and debug the ASIC long before hardware arrives
What We Need to See:
Combined network engineering depth with thorough software habits
5+ years of hands-on QA or networking experience, backed by CCNP-equivalent protocol knowledge: L2 (VLAN, STP), L3 (BGP, OSPF), EVPN, VXLAN, and advanced features like PFC, ECN, RoCE, and QoS
Production-quality Python engineering—specifically, strong OOP design and hands-on experience with Pytest
Deep Linux proficiency (at an LPIC-1 or LPIC-2 level) to navigate system internals, analyze logs, and debug effectively
Clear verbal and written communication, with professional proficiency in written and spoken English
B.Sc. or or B.A. or equivalent experience in Computer Science, Electrical Engineering, or a similar background
Ways to stand out from the crowd:
Experience with Docker and traffic generation tools (Ixia, TRex, Scapy)
Hands-on experience integrating tests into CI/CD pipelines (Jenkins, GitLab CI)
Working knowledge of virtualization platforms (KVM, VMware)
NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.
Explore more opportunities at NVIDIA