Principal Software Engineer - Networking Hyperscale Engineering

Nvidia

Actively hiring
Seattle, US · Santa Clara, US Posted 14 days ago $248,000–$391,000 / year
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At a glance

AI generated

TL;DR

NVIDIA seeks a Principal Software Engineer to join its US-based Networking Hyperscale Engineering Team, where you will collaborate with top-tier cloud and AI customers to develop high-performance networking software for AI superclusters. Your daily tasks include designing and implementing C/C++ components using DPDK and RDMA/RoCE, integrating kernel and driver features to enhance performance, and working closely with NCCL teams to optimize distributed training over NVIDIA’s network infrastructure. You will also own complex debugging efforts and participate in cross-organizational architecture discussions. Ideal candidates have 15+ years of experience in systems or networking software roles, deep C/C++ expertise, extensive knowledge of Linux kernel internals, and hands-on experience with RDMA/RoCE, GPU-related networking, and large-scale AI data center deployments.

Skills

C/C++ Linux DPDK RDMA RoCE NIC firmware DOCA NCCL BGP ECMP EVPN/VXLAN GPU-related networking GPUDirect RDMA High-performance computing Distributed training stacks Hyperscalers Cloud providers Open-source ecosystems

What you'll do

  • Design and optimize high-performance C/C++ components using DPDK and RDMA/RoCE for Linux.
  • Develop and integrate kernel, driver, and NIC firmware features to enhance AI workload performance.
  • Collaborate with NCCL teams to improve end-to-end collectives performance over NVIDIA networking.
  • Own complex debug tasks related to performance and functionality issues with customers.
  • Influence the software roadmap by working closely with top-tier cloud and AI customers.

What we're looking for

  • 15+ years of experience in systems/networking software development.
  • Deep expertise in C/C++ and Linux systems with hands-on experience in kernel networking/RDMA/NIC drivers/DPDK.
  • Proven track record developing network operating systems (NOS) and routing/switching protocols for AI data centers.
  • Practical knowledge of DOCA, NIC firmware interfaces, and hardware-accelerated networking stacks for large-scale systems.
  • Strong background optimizing NCCL or other distributed training stacks on GPU clusters for performance.
  • Experience collaborating with hyperscalers or major cloud providers on strategic AI networking deployments.

Market check

Salary context

This $248,000–$391,000 range sits above 96% of similar postings on FindRole.

Peer median band

$143,000–$241,400

Median floor and ceiling across peers.

Typical midpoint (25–75%)

$161,500–$221,725

Middle half of comparable postings.

Based on 240 comparable postings.

* 240 is the maximum number of comparable postings sampled.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 801 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 797 roles with salary data.

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