NVIDIA
AI
SeniorSoftwareEngineer,DistributedSystemsEngineer-DGXCloud
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Software Engineer, Distributed Systems Engineer - DGX Cloud at NVIDIA. Skills: Distributed Systems, AI Infrastructure, GPU Clusters, Scalable Platform Development, System Reliability and Performance. Production systems that enable large scalable GPU clusters to be used for a variety of AI workloads. Designing and developing a massively distributed scalable platform which would be used to identify, diagnose and remediate non-performant GPU assets”
What You'll Achieve.
Advance NVIDIA's capacity to build and deploy leading infrastructure solutions for a broad range of AI-based applications; Ensure production AI clusters run reliability and consistently with maximum performance
Industry & Context.
Identify, diagnose and remediate non-performant GPU assets; Evaluating system failures
What They're Looking For.
Must Have
Direct experience in a software engineering role within a highly technical organization with demonstrable impact from your work, Highly motivated with communication skills, you can work successfully with multi-functional teams, principles, and architects and coordinate effectively across organizational boundaries and geographies, 12+ years in similar role and experience on large-scale production systems, Experience with common software engineering principles, tools and techniques, 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
Nice to Have
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, Base Command Manager), Prior experience in asynchronous workflows and/or event driven architecture, Proven operational excellence in maintaining reliable and performant infrastructure
What You'll Do.
Production systems that enable large scalable GPU clusters to be used for a variety of AI workloads
Designing and developing a massively distributed scalable platform which would be used to identify
diagnose and remediate non-performant GPU assets
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
How You'll Work.
Team & Collaboration
Work successfully with multi-functional teams, principles, and architects; Coordinate effectively across organizational boundaries and geographies; Working with teams across NVIDIA
Communication Scope
Communication skills
Full Job Description
NVIDIA is hiring experienced software engineers to help scale up its AI Infrastructure. We expect you to have significant software engineering experience with cluster operations, operator development, node health monitoring and working with GPU resource scheduling. 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 GPUs, 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. * Designing and developing a massively distributed scalable platform which would be used to identify, diagnose and remediate non-performant GPU assets. * 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 software engineering 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
Applying for this Senior Software Engineer, Distributed Systems Engineer - DGX Cloud role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Workday
- Workday has a multi-step form — save your progress after every section.
- "Apply With LinkedIn" can fail or lose data; manual entry is more reliable.
- Watch for the "Submit for Review" final step — hitting "Save" alone does not submit.
- Job requisition numbers are useful when following up with HR by email.
ANONYMOUS · UNFILTERED
What do employees actually say about NVIDIA?
Real rants from real employees. Read before you apply.