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Nvidia Data Centers Jobs (NOW HIRING)

Nvidia

OR · On-site

... NVIDIA's goal of leading the next computing era! What you'll be doing: * Collaborate with product owners and technical leads to identify and collect requirements for next-generation data centers.

Nvidia

OR · On-site

As a key member of the NVIDIA Infrastructure Specialists SolutionsArchitecture team, your role ... Implementing tasks related to network configuration and validation for data centers. * Create ...

Nvidia

Senior Site Reliability Engineer

Santa Clara, CA

$67 - $89/hr

Manage NVIDIA's on-prem infrastructure. Maintain uptime, reliability and readiness of on-prem engineering cloud spread across multiple data centers. * Guard service level agreements (SLAs) for ...

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Nvidia Data Centers information

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$46K

$165K

$243.5K

How much do nvidia data centers jobs pay per year?

As of Jun 16, 2026, the average yearly pay for nvidia data centers in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Center Engineer at Nvidia, and why are they important?

To thrive as a Data Center Engineer at Nvidia, you need a solid background in IT infrastructure, networking, and server hardware, typically supported by a relevant degree or certifications like CompTIA Server+ or Cisco CCNA. Familiarity with data center management tools, virtualization platforms, and monitoring systems is highly valued. Strong problem-solving abilities, teamwork, and effective communication are crucial soft skills in this role. These skills and qualifications are important to ensure optimal data center performance, minimize downtime, and support Nvidia's high-performance computing environments.

What are the typical challenges faced by professionals working in Nvidia Data Centers, and how can new hires prepare to address them?

Professionals working in Nvidia Data Centers often encounter challenges such as managing high-density GPU clusters, ensuring optimal cooling and power efficiency, and supporting rapid scaling for AI and high-performance computing workloads. New hires can prepare by familiarizing themselves with best practices in data center operations, gaining experience with Nvidia hardware and software solutions, and staying updated on the latest advancements in data center automation and security. Collaboration with cross-functional teams, such as network engineers and software developers, is also essential to maintain efficient operations and resolve issues quickly.

What is the difference between Nvidia Data Centers vs Data Center Network Engineers?

AspectNvidia Data CentersData Center Network Engineers
Required CredentialsIT certifications, networking, hardware knowledgeNetworking certifications (CCNA, CCNP), hardware skills
Work EnvironmentData centers, hardware installation, system managementNetwork infrastructure, troubleshooting, configuration
Employer & Industry UsageTech companies, cloud providers, hardware manufacturersData centers, telecom, enterprise IT

While Nvidia Data Centers focus on managing and maintaining Nvidia's hardware infrastructure and data center operations, Data Center Network Engineers specialize in designing, implementing, and troubleshooting network systems within data centers. Both roles require networking knowledge and certifications but differ in their primary focus—hardware and system management versus network infrastructure.

What are Nvidia Data Centers?

Nvidia Data Centers are specialized facilities that house high-performance computing infrastructure powered by Nvidia’s GPUs and related technologies. These data centers are designed to run complex workloads such as artificial intelligence, machine learning, data analytics, and high-end graphics processing. Nvidia’s data center solutions enable businesses and researchers to process and analyze massive amounts of data efficiently, supporting industries like healthcare, automotive, finance, and more. They are crucial for advancing AI research, cloud computing, and edge computing applications.
Infographic showing various Nvidia Data Centers job openings in the United States as of June 2026, with employment types broken down into 2% As Needed, 89% Full Time, 1% Temporary, and 8% Contract. Highlights an 83% Physical, 8% Hybrid, and 9% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Senior Network Architect

Senior Network Architect

NVIDIA Corporation

Santa Clara, CA • Hybrid

Other

Posted 26 days ago

Job description

NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for 30 years. It's an outstanding legacy of innovation that's motivated by extraordinary technology-and outstanding people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. Come join our team and see how you can make a lasting impact on the world!
The NVIDIA Enterprise Network Architecture team is seeking experienced candidates in the extensive domain of network architecture & engineering. This is a hands-on architecture position focused on the development and deployment of ultra-high-speed, resilient, and scalable interconnects for GPU-accelerated data centers and compute clusters. Outstanding problem-solving abilities and a comprehensive understanding of the network security protocols & standards, routing, switching, automation and deep understanding of fundamental network theory is also critical to your success at NVIDIA.
What you will be doing
  • Lead the architecture, design, and deployment of global-scale backbone and data center fabrics that serve large fleets of CPU-based compute, storage, and GPU/HPC clusters.
  • Design high-performance DC fabrics using InfiniBand and high-throughput Ethernet (RoCE and traditional IP) to support both general compute workloads and GPU-dense AI/ML training and inference environments.
  • Engineer and optimize carrier interconnects, metro and long-haul backbone, and dark-fiber systems to provide low-latency, loss-minimal connectivity between regions, super labs, and data centers.
  • Partner with systems, OS, GPU, storage, and HPC platform teams to deliver scalable, highly available network architectures that can evolve with rapid growth in both compute and GPU capacity.
  • Implement and refine network monitoring, rich telemetry, and performance-engineering practices across fabrics and backbone to detect issues early and continually improve end-to-end application experience.
  • Drive technology selection, vendor engagement, and lifecycle strategy for routing, optical, and data center switching platforms across both compute and GPU domains.
  • Define and enforce security, compliance, and reliability standards for all 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.
What we need to see
  • MS or PhD in Electrical Engineering, Computer Science, Computer Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, or equivalent experience.
  • 12+ years of experience in building, managing and supporting large scale hybrid networks, developing automation pipelines with Python, Ruby, Go or other languages used in infrastructure automation.
  • Expert in 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
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables outstanding creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for exceptional people like you to help us accelerate the next wave of artificial intelligence.
#LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 208,000 USD - 333,500 USD for Level 5, and 248,000 USD - 396,750 USD for Level 6.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until February 21, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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