Principal Software Engineer - Networking Hyperscale Engineering

Job Title

Principal Software Engineer - Networking Hyperscale Engineering

Role Summary

Design and implement high-performance networking and NIC software used in large AI superclusters. Work with cloud and AI customers and internal teams (SDK, drivers, firmware, GPU/NIC architects, and distributed training teams) to define and optimize communication paths across Linux kernel, RDMA/RoCE, DPDK, DOCA, NCCL, and NIC firmware.

Experience Level

Senior — requires 15+ years of experience in systems or networking software roles.

Responsibilities

Primary responsibilities include collaborating with customers and internal teams to design, implement, and debug networking software and communication paths for large-scale AI deployments.

• Co-develop NIC software and communication paths with strategic customers to enable and scale 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.
• Collaborate 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-organization architecture discussions.

Requirements

Must-have technical skills and experience:

• Deep expertise in C and C++ and strong Linux systems knowledge.
• Hands-on experience with kernel networking, RDMA, NIC drivers, or DPDK.
• Proven experience developing and debugging network operating systems and routing/switching protocols (for example BGP, ECMP, EVPN/VXLAN) used in data centers.
• Practical experience with DOCA, NIC firmware interfaces, or other hardware-accelerated networking stacks.
• Proven ability to diagnose and resolve complex performance and reliability issues in production-grade systems.
• Excellent communication skills and experience collaborating with customers, partners, and cross-functional engineering teams.

Nice-to-have:

• Deep knowledge of Linux kernel internals, SoC/SmartNIC/NIC embedded systems, and data center switches.
• Hands-on experience with GPUDirect RDMA, RDMA/RoCE, and low-latency data paths.
• Experience optimizing NCCL or other distributed training stacks for throughput and tail latency on large GPU clusters.
• Experience working with hyperscalers or major cloud providers on performance-critical AI networking deployments.
• Contributions to open-source networking, RDMA, DPDK, kernel, CUDA/NCCL, or related projects.

Education Requirements

A Bachelor’s, Master’s, or PhD in Software Engineering, Computer Science, Computer Engineering, Electrical Engineering, or a related field is listed as preferred — or equivalent practical experience.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.