NVIDIA is looking for outstanding software engineers to help us expand our enterprise GPU management and monitoring tools. In this role, you will work closely with the broader NVIDIA team to design and build cloud-native management agents, Kubernetes integrations, and end-to-end integration solutions that combine GPUs with the rest of the datacenter software management ecosystem. We are focused on supporting NVIDIA products across HPC, cloud, and enterprise on both bare metal and virtualized platforms as the role of GPUs in all of these environments expands. Your contributions will span many aspects of GPU system integration, including telemetry and metrics, health checks, diagnostics, configuration, and system management. These tools fill roles of both passive background monitoring and active online management with a core emphasis on operational transparency and seamless integration in customer environments. Your code will support single-node developer systems through large clusters with thousands of nodes.
To succeed, you must have a strong Linux background, familiarity with modern cloud-native systems, and a proven work ethic. You will be expected to jump in quickly and provide valuable contributions from day one. This is a dynamic work environment with many exciting opportunities awaiting. NVIDIA GPUs are central to many hot enterprise, cloud, and datacenter trends. Come join us as we craft the future of accelerated computing and AI.
What you'll be doing:
Develop and maintain distributed, robust and scalable Go programs deployed to Kubernetes environments that manage large datacenters
Develop and maintain user-space applications, containers, Go-bindings, and CLI tools.
Enable GPU management integration with the state-of-the-art open-source ecosystem, including Kubernetes and Docker.
Support internal and external users through bug fixes, documentation, and feature improvements.
Maintain high-quality products through robust test coverage.
What we need to see:
BS or higher in Computer Science or equivalent experience. 5+ years of meaningful industry experience with a strong Go and Kubernetes development background
User space development and debugging expertise in Linux environments
Experience with APIs and interface design
Outstanding written and verbal interpersonal skills. Business level English
Strong motivation and commitment to learn new skills
Ability to execute all aspects of the software development lifecycle. Ability to manage time in a fast, heavily multitasked environment
Development experience with Rust, Python and/or C, C++. Development experience with distributed systems and concurrent applications, especially in a Kubernetes environment
Experience developing and maintaining enterprise software. Experience deploying, managing, and debugging applications in a Kubernetes environment
Ways to stand out from the crowd:
Background with containers (e.g. Docker, OCI), orchestration frameworks, and logging/telemetry backends with Kubernetes monitoring stacks with tools such as Prometheus, Loki and Grafana
Experience with modern UI development in React and Node.js or similar frameworks. Experience developing Kubernetes operators or Helm charts
Experience with HPC job schedulers like Slurm or Run.AI Familiarity with Kubernetes internals. Exposure to GPU programming with CUDA. Experience with Jenkins and GitHub/GitLab CI/CD pipelines
You will also be eligible for equity and benefits.
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What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
