Senior HPC DevOps Engineer

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NVIDIA is looking for an experienced HPC DevOps and Network Engineer to help us build the supercomputers and HPC clusters of the future. As a Senior HPC DevOps Engineer, you’ll be a key player in groundbreaking advancements in artificial intelligence and GPU computing. Your expertise will drive the latest breakthroughs, providing insights on at-scale system design and tuning mechanisms for large‑scale compute runs. You will work with the latest accelerated computing and deep learning software and hardware platforms, and with many scientific researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, GPU compute, and systems specialists to architect, develop, and bring up large‑scale performance platforms.

What You’ll Be Doing

• Design, implement, and maintain large‑scale HPC/AI clusters with state‑of‑the‑art monitoring, logging, and alerting systems.
• Utilize and develop Infrastructure as Code tools to manage scalable and repeatable deployments.
• Develop and maintain CI/CD pipelines to automate deployment processes.
• Automate deployment, configuration management, and operational monitoring through scripting and tooling.
• Develop complex networking automations.
• Troubleshoot issues from bare metal to application level, ensuring system reliability and efficiency.
• Serve as a technical resource and share best practices with internal teams.
• Support R&D activities and engage in proof‑of‑concepts and proof‑of‑value exercises.

What We Need To See

• B.Sc. in Computer Science, Engineering, or a related field with 5+ years of experience.
• Deep knowledge of HPC and AI solution technologies, including CPUs, GPUs, high‑speed interconnects, and supporting software.
• Advanced proficiency in programming and scripting languages, with a solid understanding of object‑oriented programming principles.
• Familiarity with Jenkins, Ansible, Puppet/Chef.
• Excellent knowledge of Windows and Linux (Red Hat/CentOS and Ubuntu), networking, and OS‑level security.
• Deep understanding of networking protocols such as InfiniBand and Ethernet.
• Experience with job scheduling workloads and orchestration tools such as Slurm and Kubernetes.
• Background with multiple storage solutions like Lustre, GPFS, ZFS, and XFS.
• Expertise with virtual systems (VMware, Hyper‑V, KVM, Citrix).
• Familiarity with cloud platforms (AWS, Azure, Google Cloud).

Ways To Stand Out From The Crowd

• Proven networking experience or professional networking training.
• Architectural insight: Knowledge of CPU and/or GPU architecture.
• Container expertise: Understanding of Kubernetes and container‑related microservice technologies.
• GPU focus: Experience with GPU‑focused hardware/software (DGX, CUDA).
• RDMA fabrics: Background with RDMA (InfiniBand or RoCE) fabrics.

At NVIDIA, we value diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We provide reasonable accommodations to ensure all individuals can participate in the job application or interview process, perform essential job functions, and receive other benefits and privileges of employment.

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