Senior Hpc Cluster Engineer

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +2

NVIDIA is seeking a Senior HPC Cluster Engineer to design, deploy, and operate GPU Compute Clusters for EDA and HPC workloads. The role involves developing automation solutions, improving infrastructure, providing technical leadership, and supporting researchers with performance analysis and optimization.

What you'd actually do

  1. Develop and enhance our ecosystem around GPU-accelerated computing including developing scalable automation solutions.
  2. Continuously improve infrastructure provisioning, management, observability and day to day operation through automation.
  3. Provide technical leadership and strategic guidance for managing large-scale HPC systems, including the deployment of compute, networking, and storage.
  4. Foster strong customer and multi-functional partnerships to ensure consistent cluster support and rapidly adapt to evolving user needs
  5. Support our researchers to run their EDA workloads including performance analysis and optimizations.

Skills

Required

  • Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience.
  • Minimum of 5 years of proven experience crafting and operating large scale compute infrastructure, including cluster configuration managements tools such as BCM or Ansible.
  • Experience with AI/HPC job schedulers and orchestrators, such as Slurm, LSF, PBS or K8s.
  • Applied experience with AI/HPC workflows that use MPI and NCCL.
  • Proficient in using Linux including Rocky/Centos/RHEL and/or Ubuntu Linux distributions.
  • A solid understanding of container technologies such Enroot and Docker.
  • Proficiency in Python and Bash
  • Experience analyzing and tuning performance for a variety of EDA workloads.
  • Excellent problem-solving to analyze complex systems, identify bottlenecks, and implement scalable solutions.
  • Excellent communication and collaboration skills, with the ability to work effectively with various teams and individuals.

Nice to have

  • Background with NVIDIA GPUs, CUDA Programming, NCCL and MLPerf benchmarking.
  • Experience supporting EDA workloads and tools.
  • Familiarity with High-Speed Networking pertaining to HPC including InfiniBand, RDMA and RoCE.
  • Understanding of fast, distributed storage systems such as Lustre and GPFS for AI/HPC workload.
  • Familiarity with metrics collection and visualization at scale with Prometheus, OpenSearch and Grafana.

What the JD emphasized

  • Minimum of 5 years of proven experience crafting and operating large scale compute infrastructure
  • Experience with AI/HPC job schedulers and orchestrators, such as Slurm, LSF, PBS or K8s.
  • Applied experience with AI/HPC workflows that use MPI and NCCL.