Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Docker @ 3
Go @ 2
Kubernetes @ 3
Python @ 2
Java @ 2
Distributed Systems @ 3
Helm @ 3
GPU @ 3
AI @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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.
The Runtime team provides 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.
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, CustomResourceDefinitions (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
Requirements
- Currently pursuing a BS, MS, or PhD in Computer Science, Computer Engineering, or a 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
- 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
Compensation
- Internship hourly rate range: 20 USD - 71 USD (rate depends on position, location, year in school, degree, and experience)
Other details
- Applications accepted at least until June 6, 2026
- NVIDIA uses AI tools in its recruiting processes
- NVIDIA is an equal opportunity employer and committed to an inclusive work environment