DGX Cloud Kubernetes Runtime Intern - Fall 2026

NVIDIA•Us, CA

About The Position

Join NVIDIA's DGX Cloud Kubernetes Runtime team as a Software Engineering Intern and gain hands-on experience building the next generation of GPU-accelerated Kubernetes runtime distributions. As an intern on the Runtime team, you will contribute to automation systems that enable operators to seamlessly install, upgrade, and manage cluster runtime packages powering NVIDIA's AI Accelerators. You'll work alongside experienced engineers on controller systems that manage runtime components for the latest GPU architectures including GB200/GB300 and beyond, helping ensure that AI researchers and developers have reliable, secure, and performant infrastructure at their fingertips. The Runtime team is responsible for providing a Kubernetes runtime distribution that can be applied to any cluster using NVIDIA accelerators, empowering operators with automation-first, self-service tools that minimize manual effort while enhancing reliability and reproducibility.

Requirements

Currently pursuing a BS, MS, or PhD in Computer Science, Computer Engineering, or related field
Hands-on experience with Kubernetes (through coursework, personal projects, or previous internships)
Familiarity with at least one programming language such as Go, Python, or Java
Understanding of basic Kubernetes concepts including pods, deployments, services, and namespaces
Enthusiasm for learning about distributed systems, automation, and cloud infrastructure
Strong problem-solving skills and ability to work collaboratively in a team environment

Nice To Haves

Experience with Go programming language and building services or tools in Go
Familiarity with Kubernetes controllers, operators, or CustomResourceDefinitions through academic projects or personal exploration
Experience with container technologies (Docker, containerd) and package management tools (Helm, Kustomize)
Contributions to open source projects, especially in the cloud-native ecosystem
Coursework or projects involving distributed systems, system design, or infrastructure automation

Responsibilities

Contribute to the runtime controller system that manages the lifecycle of runtime packages across Kubernetes clusters under the guidance of senior engineers
Assist in building and maintaining components of the runtime builder that packages, validates, and distributes GPU operators, DRA drivers, and other accelerated compute runtime packages
Help develop and test Kubernetes controllers, CRDs, and operators that automate runtime installation and upgrade operations
Work on tooling and automation scripts that support runtime composition across different cloud providers and GPU architectures
Participate in code reviews and learn best practices for building production-grade Kubernetes systems