Senior HPC AI Cluster Engineer

3 Months ago • 5 Years + • DevOps

Job Summary

Job Description

NVIDIA seeks a Senior HPC AI Cluster Engineer to design, implement, and maintain large-scale HPC/AI clusters. Responsibilities include managing Linux workloads, developing CI/CD pipelines, automating infrastructure deployment, deploying monitoring solutions, troubleshooting system issues, and supporting R&D activities. The ideal candidate will possess deep expertise in HPC, AI technologies, Linux, networking, storage solutions (Lustre, GPFS, etc.), and automation tools (Ansible, Jenkins). Experience with various hardware and software platforms is essential.
Must have:
  • 5+ years experience
  • HPC & AI solution knowledge
  • Linux & Windows expertise
  • Job scheduling & orchestration
  • Storage solutions (Lustre, GPFS)
  • Python & Bash scripting
  • Automation & configuration tools
Good to have:
  • Cloud computing platforms
  • CPU/GPU architecture knowledge
  • Kubernetes & microservices
  • GPU hardware/software (DGX, CUDA)
  • RDMA (InfiniBand or RoCE)

Job Details

NVIDIA is looking for an experienced HPC Engineer to join the E2E software verification HPC/AI Infrastructure team. we are focused on building supercomputers and HPC clusters based on groundbreaking technologies. We are looking for an outstanding architect for a senior HPC, be a key player to the most exciting computing hardware and software to contribute to the latest breakthroughs in artificial intelligence and GPU computing. Provide 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 will be doing:

  • Design, implement and maintain large scale HPC/AI clusters with monitoring, logging and alerting

  • Manage Linux job/workload schedules and orchestration tools

  • Develop and maintain continuous integration and delivery pipelines

  • 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

  • Deploy monitoring solutions for the servers, network and storage

  • Perform troubleshooting bottom up from bare metal, operating system, software stack and application level

  • Being a technical resource, develop, re-define and document standard methodologies to share with internal teams

  • Support Research & Development activities and engage in POCs/POVs for future improvements

What we need to see:

  • A degree in Computer Science, Engineering, or a related field

  • 5+ years of experience

  • Knowledge of HPC and AI solution technologies from CPU’s and GPU’s to high speed interconnects and supporting software

  • Experience with job scheduling workloads and orchestration tools such as Slurm, K8s

  • Excellent knowledge of Windows and Linux (Redhat/CentOS and Ubuntu) networking (sockets, firewalld, iptables, wireshark, etc.) and internals, ACLs and OS level security protection and common protocols e.g. TCP, DHCP, DNS, etc.

  • Experience with multiple storage solutions such as Lustre, GPFS, zfs and xfs. Familiarity with newer and emerging storage technologies.

  • Python programming and bash scripting experience.

  • Comfortable with automation and configuration management tools such as Jenkins, Ansible, Puppet/chef

  • Deep knowledge of Networking Protocols like InfiniBand, Ethernet

  • Deep understanding and experience with virtual systems (for example VMware, Hyper-V, KVM, or Citrix)

Ways to stand out from the crowd:

  • Familiarity with cloud computing platforms (e.g. AWS, Azure, Google Cloud)

  • Knowledge of CPU and/or GPU architecture

  • Knowledge of Kubernetes, container related microservice technologies

  • Experience with GPU-focused hardware/software (DGX, Cuda)

  • Background with RDMA (InfiniBand or RoCE) fabrics

We are an equal opportunity employer and value diversity at our company. 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 will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

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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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