Principal Software Engineer, Distributed Systems Engineer - DGX Cloud

NVIDIA is hiring experienced software engineers with kubernetes experience to help scale up its AI Infrastructure. The role involves working on production systems for scalable GPU clusters, implementing monitoring capabilities, and collaborating with teams to ensure reliability and performance of AI clusters.

Responsibilities:

• 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 custom software related to scheduling GPU resources on kubernetes
• 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

Requirements:

• Direct experience in a software engineering role within a highly technical organization with demonstrable impact from your work
• Software development experience with kubernetes APIs and frameworks not just operating a cluster
• 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
• 15+ years in similar role and experience on large-scale production systems
• Experience with common software engineering 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
• 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