Job description

For over 25 years, NVIDIA has been revolutionizing computer graphics, PC gaming, and accelerated computing. It’s a distinctive heritage of innovation driven by outstanding technology—and remarkable people. Are you passionate about Kubernetes and AI and want to help build the best platform for ML/AI infrastructure? Do you thrive when your work directly empowers teams to push the boundaries of what's possible? We're the DSX Kubernetes Fleet team within NVIDIA's DGX Cloud organization - a collaborative group of cloud platform engineers, architects, and SREs who are passionate about building automation, lifecycle management, and deployment safety to our massive GPU accelerated container platform. We are empowering the world's leading AI teams to train and deploy at AI Factory scale, with resiliency and security as top priorities. We design and build APIs and workflows that thoughtfully turn high-level deployment intent into production-ready AI infrastructure management. We take pride in owning our code end-to-end, and we care deeply about the full lifecycle of AI Factory Kubernetes clusters, from provisioning through upgrades and decommissioning. We build software in the open, with a goal of enabling new AI Factories to be built at speed of light. What you will be doing: • Be part of a small, dynamic team exploring innovative ways to simplify the development, deployment, and monitoring of GPU and DPU accelerated applications. • Design and develop software for managing a fleet of Kubernetes clusters for GPUs and DPUs. • Join the core group working on Cloud Native technologies, improving NVIDIA accelerators in the Kubernetes environment. • Collaborate with engineering teams across NVIDIA to ensure seamless integration of your software. • Automate and optimize build, test, integration, and release processes for cloud-native applications. • Efficiently multitask across different projects, addressing evolving priorities effectively. What we need to see: • BS/MS in Computer Science or related field (or equivalent experience). • 10+ years of proven work experience in large scale environments. • Expert-level knowledge in systems programming languages (Go, C) with a solid grasp of Data Structures and Algorithms. • Strong understanding of Container Orchestration Systems (Kubernetes) and Container Technology. • In-depth knowledge and experience with Unix/Unix-like kernel internals, particularly Linux. • Hands-on automation experience with modern infrastructure tools and technologies. • Proven experience in setting up, maintaining, and automating continuous deployment systems. • Strong background in Cloud Computing and Distributed Software design and development. • Understanding of performance, security, and reliability in complex distributed systems. Ways to stand out from the crowd: • Extensive experience with the Go programming language. • Deep understanding of rack-scale GPU systems • Strong background with Gitlab, Argo, Flux, and other CI/CD systems. • Significant hands-on experience with Containers and Kubernetes. • Hands-on experience with container workload isolation and confidential computing. Recognized as one of the technology world’s most sought-after employers, NVIDIA provides highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until August 11, 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.

Requirements

Must-haves

Be part of a small, dynamic team exploring innovative ways to simplify the development, deployment, and monitoring of GPU and DPU accelerated applications.
Design and develop software for managing a fleet of Kubernetes clusters for GPUs and DPUs.
Join the core group working on Cloud Native technologies, improving NVIDIA accelerators in the Kubernetes environment.
Collaborate with engineering teams across NVIDIA to ensure seamless integration of your software.
Automate and optimize build, test, integration, and release processes for cloud-native applications.
Efficiently multitask across different projects, addressing evolving priorities effectively.
BS/MS in Computer Science or related field (or equivalent experience).
10+ years of proven work experience in large scale environments.
Expert-level knowledge in systems programming languages (Go, C) with a solid grasp of Data Structures and Algorithms.
Strong understanding of Container Orchestration Systems (Kubernetes) and Container Technology.
In-depth knowledge and experience with Unix/Unix-like kernel internals, particularly Linux.
Hands-on automation experience with modern infrastructure tools and technologies.
Proven experience in setting up, maintaining, and automating continuous deployment systems.
Strong background in Cloud Computing and Distributed Software design and development.
Understanding of performance, security, and reliability in complex distributed systems.
Extensive experience with the Go programming language.
Deep understanding of rack-scale GPU systems
Strong background with Gitlab, Argo, Flux, and other CI/CD systems.
Significant hands-on experience with Containers and Kubernetes.
Hands-on experience with container workload isolation and confidential computing.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until August 11, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

kubernetesaimlgoci/cd

Platform: eightfold
Effort: medium

Benefits

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