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To succeed, you must have a strong Linux background, familiarity with modern distributed 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
Business level English.
Experience with APIs and interface design
Outstanding written and verbal interpersonal skills
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
Ways to stand out from the crowd:
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
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 developing Kubernetes operators or Helm charts. Experience with HPC job schedulers like Slurm. 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 .
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