NVIDIA Logo

NVIDIA

Senior GPU and HPC Infrastructure Engineer - DGX Cloud

Posted 4 Days Ago
Be an Early Applicant
In-Office or Remote
Hiring Remotely in Santa Clara, CA
184K-357K Annually
Senior level
In-Office or Remote
Hiring Remotely in Santa Clara, CA
184K-357K Annually
Senior level
Design, build, and scale GPU/HPC AI infrastructure: automate GPU asset provisioning and lifecycle, implement monitoring and health management, manage NVLINK topology, build automated test infrastructure, and integrate software across hardware to AI training applications for high reliability and scalability.
The summary above was generated by AI

NVIDIA is hiring engineers to scale up its AI Infrastructure. We expect you to have a strong programming background, knowledge of datacenter hardware, operations, and networking, familiarity with software testing and deployment, familiarity with distributed systems, and excellent communication and planning abilities. Experience working with High Performance Computing (HPC), GPUs, and high-performance networking (RDMA, Infiniband, RoCE) are strongly preferred. We also welcome out-of-the-box thinkers who can provide new ideas with a strong execution bias. Expect to be constantly challenged, improving, and evolving for the better. You and other engineers on this team will help advance NVIDIA's capacity to build and deploy leading infrastructure solutions for a broad range of AI-based applications that affect core data science.

For two decades, we have pioneered visual computing, the art and science of computer graphics. With the invention of the GPU - the engine of modern visual computing - the field has expanded to encompass video games, movie production, product design, medical diagnosis and scientific research. Today, we stand at the beginning of the next era, the AI computing era, ignited by a new computing model, GPU deep learning.

What you will be doing:
  • We have built a comprehensive platform that automates GPU asset provisioning, configuration, and lifecycle management across cloud providers. You'll contribute to this platform to build end-to-end automation of datacenter operations, break/fix, and lifecycle management for large-scale Machine Learning systems.

  • Implement monitoring and health management capabilities that enable industry-leading reliability, availability, and scalability of GPU assets. You will be harnessing multiple data streams, ranging from GPU hardware diagnostics to cluster and network telemetry.

  • Work on software that manages NVLINK topography across GPU clusters.

  • Build automated test infrastructure that we use to qualify distributed systems for operation.

  • Work with engineering teams across NVIDIA to ensure your software integrates seamlessly from the hardware all the way up to the AI training applications.

  • You'll be constantly innovating, discovering new problems and their solutions.

What we need to see:
  • Highly motivated with strong communication skills, you have the ability to work successfully with multi-functional teams, principles and architects and coordinate effectively across organizational boundaries and geographies.

  • 10+ years of software engineering experience on large-scale production systems.

  • You possess a BS in Computer Science/Engineering/Physics/Mathematics or other comparable Degree or equivalent experience.

  • Expert level knowledge of a systems programming language (Go, Python) and a solid understanding of Data Structure and Algorithms.

  • Expert level knowledge of Linux system administration and management.

  • Understanding of cluster management systems (Kubernetes, SLURM)

  • Understanding of performance, security and reliability in complex distributed systems. Familiarity with system level architecture, data synchronization, fault tolerance and state management.

Ways to stand out from the crowd:
  • Proficiency in architecting and managing large-scale distributed systems, independent of cloud providers. Deep knowledge of datacenter operations and GPU hardware. Hands-on experience working with RDMA networking.

  • Advanced hands-on experience and deep understanding of cluster management systems (Kubernetes, SLURM.) Hands-on experience in Machine Learning Operations. Hands-on experience with Bright Cluster Manager.

  • Hands-on experience developing and/or operating hardware fleet management systems. Proven operational excellence in designing and maintaining AI infrastructure

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hard-working people on the planet working for us. If you are creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 11, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

HQ

NVIDIA Seattle, Washington, USA Office

4545 Roosevelt Way NE 6th Floor, Seattle, Washington, United States, 98105

NVIDIA Bellevue, Washington, USA Office

Bellevue, United States

NVIDIA Redmond, Washington, USA Office

Redmond, United States

Similar Jobs

An Hour Ago
In-Office or Remote
92K-164K Annually
Senior level
92K-164K Annually
Senior level
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Lead end-to-end analytical projects assessing healthcare cost, utilization, clinical, financial, and operational trends; partner with cross-functional teams to identify improvement opportunities, standardize processes, and translate complex analyses into concise, leadership-ready recommendations and presentations.
Top Skills: ExcelPowerPointSharepointTeams
6 Hours Ago
In-Office or Remote
Seattle, WA, USA
140K-185K Annually
Senior level
140K-185K Annually
Senior level
Blockchain • Fintech • Payments • Financial Services • Cryptocurrency • Web3
Lead end-to-end KYC lifecycle for complex corporate customers: onboarding, periodic and event-driven reviews, enhanced due diligence, monitoring, reporting findings, recommending risk-based actions, driving workflow standardization, and supporting KYC tooling and metrics.
Top Skills: Apple MacosBlockchainDocument RepositoriesGoogle SuiteOnboarding PlatformsScreening SolutionsSlack
7 Hours Ago
Remote or Hybrid
USA
38K-88K Annually
Mid level
38K-88K Annually
Mid level
Machine Learning • Payments • Security • Software • Financial Services
Provide first-line remote and on-site technology support for employees and contractors, troubleshoot hardware/software issues, use help-desk tools, escalate to higher-level teams, and ensure customer-focused resolution following PNC policies.

What you need to know about the Seattle Tech Scene

Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.

Key Facts About Seattle Tech

  • Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Amazon, Microsoft, Meta, Google
  • Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
  • Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Madrona, Fuse, Tola, Maveron
  • Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account