
Senior Site Reliability Engineer - Datacenter Automation
Summary
NVIDIA is seeking a Senior SRE to join its DGX Cloud team, responsible for scaling and operating large GPU clusters powering AI infrastructure. The role involves datacenter automation, observability, incident management, and lifecycle management of GPU assets across multiple cloud providers.
About the role
NVIDIA is hiring experienced SRE engineers to help scale up its AI Infrastructure. We expect you to have significant experience with site reliability principles and techniques including reliability assessments, incident management processes, production system observability, monitoring and alerting, automated deployments and toil elimination. We view SRE as a software engineering discipline and expect significant contributions to our codebase. We welcome out-of-the-box thinkers who can provide new ideas with strong execution bias. Expect to be constantly challenged, improving, and evolving for the better. You will help advance NVIDIA's capacity to build and deploy leading infrastructure solutions for a broad range of AI-based applications. If you're creative, passionate about SRE, and love having fun, please apply today!
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:
You will be part of an DGX Cloud team responsible for production systems that enable large scalable GPU clusters to be used for a variety of AI workloads. This includes working on supporting the operation of custom software related to GPU asset provisioning, configuration, and lifecycle management across many cloud providers.
Implementing 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.
Working with teams across NVIDIA to ensure production AI clusters run reliability and consistently with maximum performance. Evaluating system failures and improving services based on a well-defined incident management process.
What we need to see:
Direct experience in a DevOps/SRE role within a highly technical organization with demonstrable impact from your work.
Highly motivated with strong communication skills, you can work successfully with multi-functional teams, principles, and architects and coordinate effectively across organizational boundaries and geographies.
5+ years in similar role and experience on large-scale production systems. Experience with the aforementioned DevOps/SRE principles, tools and techniques.
You possess a BS in Computer Science, Engineering, Physics, Mathematics or a comparable Degree or equivalent experience.
Technical knowledge, including a systems programming language (Go, Python) and a solid understanding of data structures and algorithms.
Ways to stand out from the crowd:
Technical competency in managing and automating large-scale distributed systems independent of cloud providers. Advanced hands-on experience and deep understanding of cluster management systems (Kubernetes, Slurm, Bright Cluster Manager)
Proven operational excellence in maintaining reliable and performant AI infrastructure.
What you'll do
Requirements
Nice to have
Role overview
Tech stack analysis
Salary estimate
NVIDIA is a top-tier semiconductor/AI company headquartered in Santa Clara, CA. Senior SRE roles at NVIDIA with 5+ years of experience and specialized GPU/AI infrastructure expertise typically command $175K–$240K base salary, consistent with Levels.fyi and Glassdoor data for NVIDIA L5/L6-equivalent SRE positions. Total compensation including RSUs and bonus is likely $300K–$450K+.
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Sign up free →NVIDIA is the world's leading designer of GPUs and AI computing platforms. Its chips power everything from gaming and data centers to autonomous vehicles and scientific research. With a market cap exceeding $2 trillion, NVIDIA's CUDA platform and AI accelerators have become the backbone of the global AI revolution.