About The Position
Join NVIDIA's Accelerated 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 engineers to seamlessly install, upgrade, and manage cluster runtime packages powering NVIDIA's AI Accelerators. You'll work on innovative controller systems that optimize runtime components for the latest GPU architectures including GB200/GB300, Vera Rubin and beyond, ensuring that AI researchers and developers have reliable, secure, and performant infrastructure at their fingertips. The Runtime team is responsible for providing an NVIDIA-Accelerated Kubernetes runtime that can be applied to any cluster using NVIDIA accelerators, empowering engineers with automation-first, self-service tools that minimize manual effort while enhancing reliability and reproducibility. 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!
Requirements
- Bachelors in Computer Science, or equivalent experience
- 8+ years of professional experience, with at least 3 years of experience with Kubernetes development
- Experience building production Kubernetes systems with significant 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
- Demonstrated ability to design and implement automation systems that replace manual processes with reliable, self-service tooling
Nice To Haves
- Experience working with NVIDIA Kubernetes components such as GPU operator, device plugins, or other HPC components in large scale production environments
- Deep familiarity with OCI registries, artifact signing, SBOM generation, and supply chain security practices
- Experience building multi-tenant platform services with focus on API design, versioning, and backward compatibility
- Track record of migrating legacy systems to modern, automated platforms while maintaining zero-downtime operations and contributions to upstream Kubernetes/CNCF projects or experience extending Kubernetes API machinery
- Deep understanding of Kubernetes architecture including API machinery, admission controllers, and resource lifecycle management
Responsibilities
- Design and implement runtime features that orchestrate the lifecycle of runtime components across thousands of Kubernetes clusters without manual intervention
- Build and maintain the systems that configure, package, validate, and distribute accelerated compute components
- Develop Kubernetes controllers, CRDs, and operators that automate runtime installation, upgrade, and rollback operations with API driven workflows
Benefits
- You will also be eligible for equity and benefits .
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees
