NVIDIA
Networking
PrincipalSoftwareEngineer-Networking
Neural analysis suggests this role is
optimal for Lead candidates.
“Principal Software Engineer - Networking at NVIDIA. Skills: Networking, AI Superclusters, High-performance networking stack, Linux kernel, RDMA/RoCE, DPDK, DOCA, NCCL, NIC firmware, C/C++, Linux, GPU/NIC platforms. Co-developing NIC software and communication paths with strategic, top-tier customers to enable and scale large AI superclusters. Designing and implementing high‑performance C/C++ components on Linux using DPDK, kernel-bypass techniques, and RDMA/RoCE”
What You'll Achieve.
Influence NVIDIA’s NIC software roadmap; Design and optimize the NIC and communication paths for next-generation GPU and NIC platforms; Define their role in the modern AI data center; Enable and scale large AI superclusters; Improve throughput, latency, and reliability for AI workloads; Tune end-to-end collectives performance over NVIDIA networking at scale
Industry & Context.
Owning complex performance and functionality debug
What They're Looking For.
Must Have
15+ years overall experience in a similar or related systems / networking software role, A 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, Linux systems knowledge, 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 (for example BGP, ECMP, EVPN/VXLAN), Practical experience with DOCA, NIC firmware interfaces, or other hardware-accelerated networking stacks for large-scale systems, Excellent communication skills, A track record of effective collaboration with developers, partners, and customers in dynamic environments
Nice to Have
Deep knowledge of Linux kernel / systems internals, SoC / SmartNIC / NIC embedded systems knowledge, Data center switches and NOS knowledge, Hands-on experience with RDMA/RoCE, Hands-on experience with GPU-related networking (for example GPUDirect RDMA), Hands-on experience with 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
What You'll Do.
Co-developing NIC software and communication paths with strategic
top-tier customers to enable and scale large AI superclusters
Designing and implementing high‑performance C/C++ components on Linux using DPDK
kernel-bypass techniques
Developing and integrating kernel
and NIC firmware features to improve throughput
and reliability for AI workloads
Working closely with NCCL and distributed training teams to tune end-to-end collectives performance over NVIDIA networking at scale
Owning complex performance and functionality debug with customers
Representing the team in cross-org architecture discussions
How You'll Work.
Team & Collaboration
Work directly with top-tier cloud and AI customers; Co-develop software that powers their AI superclusters; Work closely with SDK, driver, firmware, and GPU/NIC architects; Work with domain experts in large-scale training, collectives, and systems performance; Collaboration with developers, partners, and customers in dynamic environments
Communication Scope
Excellent communication skills
Full Job Description
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. **What you 'll be doing:** * Co-developing NIC software and communication paths with strategic, top-tier customers to enable and scale large AI superclusters. * Designing and implementing high‑performance C/C++ components on Linux using DPDK, kernel-bypass techniques, and RDMA/RoCE. * Developing and integrating kernel, driver, and NIC firmware features to improve throughput, latency, and reliability for AI workloads. * Working closely with NCCL and distributed training teams to tune end-to-end collectives performance over NVIDIA networking at scale. * Owning complex performance and functionality debug with customers and representing the team in cross-org architecture discussions. **What we need to see:** * 15+ years overall experience in a similar or related systems / networking software role. * A 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 ne
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