below marketmost similar roles pay hereabove market
This role pays more than
92%
of similar roles. Most pay
$149,500–$208,800
— the blue band above.
At the midpoint, this role pays about
$236k
versus about
$179k
for comparable roles.
Based on 240 similar postings.
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
1623 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 1110 roles with salary data.
Senior Software Engineer, AI Networking joins the US-based networking software team as a technical leader focused on transforming AI networking systems. The role involves architecting, designing, and developing scalable, high-performance hardware-accelerated software solutions for the BlueField DPU and ConnectX product lines. Key responsibilities include leading deep technical engagements with hyperscalers, managing design-in, coding, bring-up, performance tuning, and failure analysis. The candidate will translate customer needs into product features, reference architectures, and firmware roadmap items. Required skills include deep knowledge of networking protocols, distributed systems, RoCE/InfiniBand, and L1–L4 fundamentals. Technical proficiency in C/C++ for low-level software, debugging across firmware and OS, and experience with RDMA verbs, DPDK, DOCA, NCCL, and CUDA-aware networking are essential for solving complex performance and latency tradeoffs.
What does a Software Engineer earn in Washington?
Median $202800 from 409 postings across 38 companies.
Architect, design, and develop scalable, high-performance hardware-accelerated software solutions.
Lead deep technical engagements with hyperscalers including design-in, coding, bring-up, and performance tuning.
Establish technical expertise in AI networking products, specifically BlueField DPU and ConnectX lines.
Translate customer needs into product features, reference architectures, tooling, and technical guidelines.
Drive performance, reliability, and debuggability improvements across customer software stacks.
Convert technical findings into actionable product, firmware, and software roadmap items.
Manage complex customer engagements to influence product and architecture direction.
What we're looking for
Bachelor’s, Master’s, or PhD in Software Engineering, Computer Science, Computer Engineering, Electrical Engineering, or a related science degree (or equivalent experience).
8+ years of relevant industry experience, including technical leadership across complex systems.
Deep knowledge of networking protocols and distributed systems, including RoCE/InfiniBand, L1–L4 fundamentals, and performance/latency tradeoffs.
Proficiency in C/C++ with experience debugging across firmware, driver, OS, and application layers.
Demonstrated experience in high-performance networking and system-level debugging, including packet drops, retransmissions, congestion, QoS, ordering, and buffer management.
Excellent interpersonal skills to explain complex topics to engineers, PMs, and customer collaborators while aligning cross-organizational teams.
Prior experience in customer-facing technical leadership at hyperscalers/CSPs (preferred).
Hands-on expertise with RDMA verbs, DPDK, DOCA, NCCL, CUDA-aware networking, congestion control, and performance tuning at scale (preferred).
C/C++
RoCE
InfiniBand
RDMA
DPDK
DOCA
NCCL
CUDA
Networking Protocols
Distributed Systems
Firmware
OS
Performance Tuning
Congestion Control
QoS
Telemetry
Automation
C
Python
Linux
Ethernet Networking
TCP/IP
BGP
EVPN-VxLAN
SONiC
Cumulus Linux
Network Operating Systems
Switch Pipelines
ACLs
Bluefield
ConnectX
Spectrum Switches
C/C++
RDMA
RoCE
InfiniBand
DPDK
DOCA
NCCL
CUDA
Networking Protocols
Distributed Systems
Firmware
Performance Tuning
Congestion Control
QoS
Telemetry
Automation
C
Python
Linux
InfiniBand
NVLink
Spectrum-X
DPDK
SRIOV
SDN
NIC Drivers
DPUs
SmartNICs
Embedded Firmware
CUDA
NCCL
MPI
DOCA
Network Operating Systems
HPC
IPC