Senior Software Engineer, Network System Validation

About this role

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. Within NVIDIA , the Networking Business Unit (NBU) builds the high-speed interconnect — Ethernet, InfiniBand, NVLink, and BlueField DPUs — that switches thousands of GPUs into a single AI supercomputer, moving data at the scale and speed the most demanding workloads require.

We are looking for a Technical Lead to join our Network System Validationgroup. You will work on validating advanced networking solutions across NVIDIA complex AI cluster environments. The group is a high-performance engineering force that treats validation as a first-class software problem. We build systems, frameworks, and benchmarks that prove our network's correctness and performance at scale. In this role you will lead the validation direction and engineering excellence of one of our technology validation teams.

This is a deeply hands-on role for a technology leader who can own the technical roadmap, technology mentoring a team of high-performance engineers, and push NVIDIA 's network to its speed-of-light limits. The role combines the development of validation methodologies and automation tools with hands-on debugging, performance analysis, and investigation of cutting-edge AI networking technologies at scale. What you’ll be doing: Review system and product requirements, design validation methodologies, develop and implement comprehensive test plans, functional and performance, for networking technologies in large-scale AI cluster solutions Develop and maintain benchmarks, automation tools and scripts for test execution, environment setup, log collection, and data analysis.

Lead end-to-end investigation of complex issues by reproducing real-world scenarios, analyzing logs, telemetry, packet captures, and system metrics to identify functional issues and performance bottlenecks, triaging problems across the hardware and software stack, and driving them to root cause and resolution Read and understand source code (C/C++/Python) to investigate defects, validate fixes, and improve logging, instrumentation, and debugging capabilities Collaborate deeply with software and hardware development teams to debug networking technologies, including NCCL, RoCE, RDMA, and related software components using targeted experiments and code inspection Profile and research AI training and inference workloads, correlating application behavior with network and system telemetry to identify scalability and performance limitations Document findings, communicate technical results, and continuously improve validation methodologies, automation environments, and engineering processes What we need to see: B.Sc.