Join NVIDIA's DGX Cloud Kubernetes Runtime team and be at the forefront of building the next generation of GPU-accelerated Kubernetes runtime distributions. As a Software Engineer on the Runtime team, you will design and build automation systems that enable operators to seamlessly install, upgrade, and manage cluster runtime packages powering NVIDIA's AI Accelerators. You'll work on innovative controller systems that manage runtime components for the latest GPU architectures including GB200/GB300 and beyond, ensuring 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

Design and implement the runtime controller system that manages the lifecycle of runtime packages across thousands of Kubernetes clusters without manual pipeline intervention
Build and maintain the runtime builder that packages, validates, and distributes GPU operators, DRA drivers, network components, and other accelerated compute runtime packages
Develop Kubernetes controllers, CRDs, and operators that automate runtime installation, upgrade, and rollback operations with API driven workflows
Create expansion rules and component management systems that enable flexible runtime composition across different cloud providers and GPU architectures
Work with internal teams to migrate from GitLab pipeline-based deployments to fully automated, controller powered runtime management

What We Need To See

Experience building production Kubernetes systems with deep expertise in controllers, operators, and CustomResourceDefinitions
Strong proficiency in Go and experience building scalable Go services that manage complex distributed systems
Hands-on experience with Helm, Kustomize, and managing Kubernetes manifest packaging and templating at scale
Deep understanding of Kubernetes architecture including API machinery, admission controllers, and resource lifecycle management
Demonstrated ability to design and implement automation systems that replace manual processes with reliable, self-service tooling
Masters and/or PhD in Computer Science, or equivalent experience
15+ years of professional experience, with at least 4 years experience with Kubernetes development

Ways To Stand Out From The Crowd

Experience building multi-tenant platform services with focus on API design, versioning, and backward compatibility
Deep familiarity with OCI registries, artifact signing, SBOM generation, and supply chain security practices
Experience working with GPU operators, device plugins, or other hardware acceleration components in Kubernetes
Track record of migrating legacy systems to modern, automated platforms while maintaining zero-downtime operations
Contributions to upstream Kubernetes projects or experience extending Kubernetes API machinery

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for great people like you to help us accelerate the next wave of artificial intelligence. NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're a creative, curious, and driven technical leader, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 425,500 USD.

You will also be eligible for equity and benefits .

Applications for this job will be accepted at least until November 10, 2025.NVIDIA is committed to fostering a diverse 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.

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