NVIDIA is the world leader in computer graphics, artificial intelligence, and accelerated computing. For over 25 years, we have been at the forefront of research and engineering around the greatest advances in technology. Our history of innovation drives us to solve the worlds hardest problems.NVIDIA is looking for Senior Cloud Infrastructure/DevOps Solutions Architect to join its NVIDIA Infrastructure Specialist Team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centers. Join the team building many of the largest and fastest AI/HPC systems in the world! We are looking for someone with the ability to work on a dynamic customer focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners and internal teams, to analyze, define and implement large scale Networking projects. The scope of these efforts includes a combination of Networking, System Design and Automation and being the face to the customer!What youll be doing:<ul><li>Maintain large scale HPC/AI clusters with monitoring, logging and alerting Manage Linux job/workload schedulers and orchestration tools.</li><li>Develop and maintain continuous integration and delivery pipelines</li><li>Develop tooling to automate deployment and management of large-scale infrastructure environments, to automate operational monitoring and alerting, and to enable self-service consumption of resources.</li><li>Deploy monitoring solutions for the servers, network and storage.</li><li>Perform troubleshooting bottom up from bare metal, operating system, software stack and application level.</li><li>Being a technical resource, develop, re-define and document standard methodologies to share with internal teams Support Research &amp; Development activities and engage in POCs/POVs for future improvements .</li></ul>What we need to see:<ul><li>BS/MS/PhD or equivalent experience in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields.</li><li>At least 8 years of professional experience in networking fundamentals, TCP/IP stack, and data center architecture.</li><li>Knowledge of HPC and AI solution technologies, including CPUs, GPUs, high-speed interconnects, and supporting software.</li><li>Extensive knowledge and hands-on experience with Kubernetes, including container orchestration for AI/ML workloads, resource scheduling, scaling, and integration with HPC environments.</li><li>Experience in managing and installing HPC clusters, including deployment, optimization, and troubleshooting.</li><li>Experience with job scheduling workloads and orchestration technologies such as Slurm, Kubernetes, and Singularity.</li><li>Excellent knowledge of Windows and Linux systems (Redhat/CentOS and Ubuntu), including internals, ACLs, OS-level security protections, and common protocols like TCP, DHCP, DNS, etc.</li><li>Experience with multiple storage solutions, including Lustre, GPFS, ZFS, and XFS. Familiarity with newer and emerging storage technologies is a plus.</li><li>Proficiency in Python programming and bash scripting.</li><li>Knowledge of CI/CD pipelines for software deployment and automation.</li><li>Comfortable with automation and configuration management tools, including Jenkins, Ansible, Puppet/Chef, etc.</li><li>Ability to communicate technical concepts and collaborate effectively with Japanese-speaking customers.</li></ul>Ways to stand out from the crowd:<ul><li>Knowledge of CPU and/or GPU architecture .</li><li>Knowledge of Kubernetes, container related microservice technologies.</li><li>Experience with GPU-focused hardware/software (DGX, CUDA.)</li><li>Background with RDMA (InfiniBand or RoCE) fabrics.</li></ul>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 individuals in the world working for us. If youre creative and autonomous, we want to hear from you.

NVIDIA

Senior Solutions Architect, Cloud Infrastructure and DevOps - NVIS

NVIDIA

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