Principal Software Engineer - Networking Hyperscale Engineering

NVIDIA is looking for an experienced Principal Software Engineer to expand the US-based Networking Hyperscale Engineering Team. Are you craving an opportunity to work directly with top-tier cloud and AI customers, co‑develop software that powers their AI superclusters, and influence NVIDIA’s NIC software roadmap? In this role you will do just that for NVIDIA’s high‑performance networking stack spanning Linux kernel, RDMA/RoCE, DPDK, DOCA, NCCL, and NIC firmware. You will be among the first to design and optimize the NIC and communication paths for our next‑generation GPU and NIC platforms and help define their role in the modern AI data center. You’ll work closely with some of the best SDK, driver, firmware, and GPU/NIC architects in the industry, as well as domain experts in large‑scale training, collectives, and systems performance. Responsibilities Co‑develop NIC software and communication paths with strategic, top‑tier customers to enable and scale large AI superclusters. Design and implement high‑performance C/C++ components on Linux using DPDK, kernel‑bypass techniques, and RDMA/RoCE. Develop and integrate kernel, driver, and NIC firmware features to improve throughput, latency, and reliability for AI workloads. Work closely with NCCL and distributed training teams to tune end‑to‑end collectives performance over NVIDIA networking at scale. Own complex performance and functionality debugging with customers and represent the team in cross‑org architecture discussions. Qualifications 15+ years overall experience in a similar or related systems / networking software role. Bachelor’s, Master’s or PhD in Software Engineering, Computer Science, Computer Engineering, Electrical Engineering, or a related field (or equivalent experience). Deep C/C++ expertise, strong Linux systems knowledge, and hands‑on experience with kernel networking / RDMA / NIC drivers or DPDK. Proven experience developing and debugging network operating systems (NOS) and routing/switching protocols used in AI data centers (e.g., BGP, ECMP, EVPN/VXLAN). Practical experience with DOCA, NIC firmware interfaces, or other hardware‑accelerated networking stacks for large‑scale systems. Excellent communication skills and a track record of effective collaboration with developers, partners, and customers in dynamic environments. Ways to Stand Out Deep knowledge of Linux kernel / systems internals, SoC / SmartNIC / NIC embedded systems, and data center switches and NOS. Hands‑on experience with RDMA/RoCE, GPU‑related networking (e.g., GPUDirect RDMA), and high‑performance, low‑latency data paths. Background optimizing NCCL or other distributed training stacks on large GPU clusters for throughput and tail latency. Experience working with hyperscalers or major cloud providers on strategic, performance‑critical AI networking deployments. Contributions to open‑source networking, RDMA, DPDK, kernel, CUDA/NCCL, or related ecosystems. Compensation & Benefits Base salary range: 272,000 USD – 431,250 USD, dependent on location, experience, and internal peer comparison. Eligible for equity and benefits. Applications for this job will be accepted at least until July4,2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA. #J-18808-Ljbffr NVIDIA