Used Tools & Technologies
Machine LearningRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Security @ 4
Go @ 4
Ruby @ 4
Python @ 4
Statistics @ 4
Data Science @ 4
Mathematics @ 4
Networking @ 4
Compliance @ 4
GPU @ 4
AI @ 4
InfiniBand @ 4
HPC @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA is seeking an experienced network architect to design and deploy ultra-high-speed, resilient, and scalable interconnects for GPU-accelerated data centers and compute clusters. This is a hands-on architecture and engineering role that partners with systems, OS, GPU, storage, and HPC platform teams to deliver highly available network architectures for large-scale AI, HPC, and enterprise workloads.
Responsibilities
- Lead the architecture, design, and deployment of global-scale backbone and data center fabrics serving CPU-based compute, storage, and GPU/HPC clusters.
- Design high-performance data center fabrics using InfiniBand and high-throughput Ethernet (RoCE and traditional IP) to support general compute and GPU-dense AI/ML training and inference.
- Engineer and optimize carrier interconnects, metro and long-haul backbone, and dark-fiber systems for low-latency, loss-minimal connectivity between regions, super labs, and data centers.
- Implement and refine network monitoring, rich telemetry, and performance-engineering practices across fabrics and backbone to detect issues early and improve end-to-end application experience.
- Drive technology selection, vendor engagement, and lifecycle strategy for routing, optical, and data center switching platforms.
- Define and enforce security, compliance, and reliability standards for backbone and fabric components supporting sensitive enterprise and R&D workloads.
- Collaborate with internal product and engineering teams to develop "NVIDIA on NVIDIA" reference architectures and best-practice solutions for large-scale compute and AI data centers.
Requirements
- MS or PhD in Electrical Engineering, Computer Science, Computer Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, or equivalent experience.
- 12+ years of experience building, managing, and supporting large-scale hybrid networks.
- Experience developing automation pipelines using Python, Ruby, Go, or other infrastructure automation languages.
- Expert knowledge of networking technologies: TCP/UDP, IPv4/IPv6, BGP/MP-BGP, VPN, L2 switching, EVPN, VxLAN, Segment Routing, MPLS, IS-IS, DWDM.
- Experience automating SDN/NFV/NFVI infrastructure.
- Strong problem-solving skills and a deep understanding of network security protocols & standards, routing, switching, automation, and fundamental network theory.
Compensation & Benefits
- Base salary range (by level):
- Level 5: 208,000 USD - 333,500 USD
- Level 6: 248,000 USD - 396,750 USD
- Eligible for equity and company benefits (see company benefits page).
Additional Information
- #LI-Hybrid
- Applications accepted at least until February 21, 2026.
- NVIDIA uses AI tools in its recruiting process and is an equal opportunity employer committed to diversity and non-discrimination.