Nvidia Cloud Platform Engineer 

India, Karnataka, Bengaluru 

273341534

The systems you operatewill support single-node developer systems through large clusters with thousands of nodes deployed on multiple Cloud providers.

To succeed, you must have a strong system and software development background, familiarity with modern distributed systems especially the Cloud-native ecosystem, 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:

• Enable GPU provisioning and life-cycle with state-of-the-art Cloud-Native open-source ecosystem solutions, including Kubernetes, Docker, Prometheus, TerraForm and Crossplane.

• Develop, maintain and/or operate robust, scalable Go programs in a Kubernetes environment.

• Develop the next-generation multi-cloud infrastructure management systems to support GenAI.

• Support internal and external users through bug fixes, documentation, and feature improvements.

• Maintain high-quality products through robust test coverage and Day 2 capabilities..

What we need to see:

• BS or higher in Computer Science or equivalent experience.

• 5+ years of meaningful industry experience with a strong Kubernetes and DevOps background

• Deep understanding and execution skills of all aspects of the software development lifecycle

• Experience with OpenAPI and Kubernetes Custom Resource Definitions

• Outstanding written and verbal interpersonal skills

• Strong motivation and commitment to learn new skills

• Ability to manage time in a fast, heavily multitasked environment

Ways to stand out from the crowd:

• Open Source contributions to the Cloud-Native community.

• Strong experience with GitHub/GitLab CI/CD pipelines and application configuration..

• Strong knowledge of container technologies, orchestration frameworks and observability systems.

• Exposure to GPU programming with CUDA a plus.

• Experience with managing and operating HPC schedulers and/or working across multiple Cloud providers.