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Remote role and broad infrastructure requirements increase competition, but senior specialization tempers applicant density.
Highly specialized AI/GPU and enterprise storage experience limits cross-industry transferability.
Many mandatory specialized skills (BMaaS, Ceph, GPU, hardware) impose strict screening.
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Design, deploy, operate, and troubleshoot large-scale Linux-based bare metal infrastructure including servers, GPU clusters, and enterprise storage platforms.
Manage GPU-accelerated AI/ML infrastructure focusing on provisioning, performance optimization, and lifecycle management of NVIDIA GPU technologies.
Ensure operational excellence and reliability of enterprise Linux infrastructure supporting HPC and AI Factory environments, including networking and storage solutions.
Expert-level Linux administration skills with Ubuntu mandatory; Red Hat and SUSE preferred.
Deep hands-on experience with bare metal infrastructure including server hardware management (BIOS/UEFI, RAID, firmware, iLO/iDRAC/IPMI, NICs).
Experience managing GPU infrastructure for AI workloads, specifically NVIDIA GPUs such as A100, H100, DGX servers.
Advanced knowledge of enterprise storage systems (Ceph, LVM, NFS, iSCSI, Fibre Channel SAN) and high-performance networking (100G+ Ethernet, VLANs, RoCE, RDMA).
Professional with substantial experience designing and operating large-scale enterprise Linux and bare metal environments focused on AI and HPC workloads.
Candidate with deep understanding of GPU-enabled infrastructure lifecycle management, NVIDIA ecosystem technologies, and high-performance storage.
Expertise in end-to-end infrastructure operations including hardware diagnostics, networking, storage tuning, and automation using Bash/Python scripting.