Senior HPC Cluster Administrator – Deep Learning Frameworks

AdministrationAdministrationFull TimeRemoteSeniorTeam 10,001+Since 1993H1B SponsorCompany SiteLinkedIn

Location

Poland

Posted

2 days ago

Salary

zł221.3K - zł507K / year

Seniority

Senior

Job Description

Senior HPC Cluster Administrator – Deep Learning Frameworks

NVIDIA

• Own the full lifecycle of GPU compute clusters — procurement, provisioning, configuration management, monitoring, and deprecation — across heterogeneous Linux environments (DGX, HGX, embedded systems) • Design and scale storage solutions (NFS, Lustre, WekaFS, or equivalent) with a clear roadmap for capacity and performance growth • Lead automation of infrastructure using modern IaC tools (Ansible, Terraform) and CI/CD pipelines (GitLab) • Manage and optimize job scheduling via Slurm, including fair-share policies, reservation management, and MIG/GPU partitioning strategies • Maintain and improve observability stacks (Prometheus, Grafana, DCGM) and drive proactive resolution of hardware and software incidents • Collaborate with ML engineers and software teams to tune cluster configuration for large-scale distributed training workloads • Evaluate and introduce new technologies — networking fabrics (InfiniBand, NVLink, EFA/RDMA), storage tiers, container runtimes — to improve performance and reliability • Mentor junior engineers and contribute to team-wide engineering standards

Job Requirements

  • BS/MS in CS, EE, CE, or equivalent hands-on experience
  • 5+ years of experience deploying and administering large-scale HPC or ML training clusters
  • Deep expertise in Linux systems administration at scale
  • Strong scripting and automation skills in Python and/or bash
  • Hands-on experience with Slurm (scheduling, accounting, cgroup configuration)
  • Proficiency with configuration management and IaC (Ansible required; Terraform a plus)
  • Experience with container technologies (Docker, Apptainer/Singularity, Kubernetes)
  • Solid understanding of high-speed networking (InfiniBand, RoCE, RDMA, EFA)
  • Experience with distributed/parallel filesystems and storage architecture
  • Ability to own problems end-to-end and communicate clearly with engineering and management stakeholders

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