Job Description

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.

What you will be doing:

• 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

What we need to see:

• 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

Ways to stand out from the crowd:

• 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

Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 20 USD - 71 USD.

You will also be eligible for Internbenefits ​

Applications for this job will be accepted at least until June 6, 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.