Senior HPC DevOps Engineer

4 Months ago • 5 Years + • DevOps

Job Summary

Job Description

NVIDIA seeks a Senior HPC DevOps Engineer to design, implement, and maintain large-scale HPC/AI clusters. Responsibilities include developing and maintaining CI/CD pipelines, automating deployment and configuration management, deploying advanced monitoring solutions, troubleshooting complex issues, and serving as a technical resource. The ideal candidate possesses deep knowledge of HPC and AI technologies, expertise in scripting languages, familiarity with various tools (Jenkins, Ansible, etc.), and experience with diverse storage and virtualization solutions. The role involves working with cutting-edge hardware and software platforms and collaborating with researchers and developers on groundbreaking advancements in AI and GPU computing.
Must have:
  • 5+ years HPC/AI experience
  • Proficiency in scripting/programming
  • Knowledge of HPC/AI technologies
  • CI/CD pipeline development
  • Experience with various tools (Jenkins, Ansible etc.)
  • Troubleshooting and monitoring expertise
Good to have:
  • CPU/GPU architecture knowledge
  • Kubernetes and container experience
  • GPU hardware/software expertise (DGX, CUDA)
  • RDMA (InfiniBand or RoCE) fabrics experience

Job Details

NVIDIA is looking for an experienced HPC DevOps 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 specialist to architect, develop and bring up large scale performance platforms.

What you’ll be doing:

  • Innovate and Implement: Design, implement, and maintain large-scale HPC/AI clusters with state-of-the-art monitoring, logging, and alerting systems.

  • Infrastructure as Code (IaC): Utilize and develop tools to manage infrastructure as code, ensuring scalable and repeatable deployments.

  • Streamline CI/CD Pipelines: Develop and maintain continuous integration and continuous delivery (CI/CD) pipelines to automate and streamline deployment processes.

  • Automate Everything: Develop automation scripts and tools to automate deployment, configuration management, and operational monitoring.

  • Enhance Monitoring: Deploy advanced monitoring solutions for servers, networks, and storage to ensure seamless operations.

  • Troubleshoot Complex Issues: Perform comprehensive troubleshooting from bare metal to application level, ensuring system reliability and efficiency.

  • Lead and Educate: Serve as a technical resource, developing and sharing best practices with internal teams.

  • Drive Innovation: Support R&D activities and engage in proof of concepts (POCs) and proof of values (POVs) for future improvements.

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 (Redhat/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.

  • Experience 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:

  • 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. Join us and be part of a team that's pushing the boundaries of technology and making a real impact in the world.

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About The Company

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

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