Data Centre Systems Engineer

What You'll Do

Deploy, rack, cable and maintain

GPU servers, compute nodes and storage systems

within a Melbourne. Support new infrastructure build-outs, including physical installation, fibre and high-density cabling, and commissioning of large-scale GPU clusters. Perform hardware troubleshooting, firmware upgrades and lifecycle management across bare-metal and GPU infrastructure. Deploy and support network/fabric hardware, including switches and fibre-optic infrastructure. Work alongside Network and AI Operations Engineers to integrate compute infrastructure into production environments. Provide

Level 2 infrastructure support

and contribute to documentation, runbooks, on-call processes and the continued development of 24/7 operations. Monitor system health and performance across physical and virtualised infrastructure. Work directly with major technology vendors during hardware incidents, troubleshooting and RMA processes. Maintain accurate asset records, network diagrams and change-management documentation. Gain exposure to

infrastructure-as-code and automation practices

as the platform continues to scale. What You'll Bring

Hands-on experience working with

enterprise server hardware in a data centre environment , including racking, cabling, deployment and troubleshooting. Experience within a

hyperscaler, large-scale data centre operator or major enterprise environment

would be highly regarded. Exposure to network and fabric deployment, including

switch installation, fibre-optic diagnostics and structured cabling . Working knowledge of

Linux systems administration

and server configuration. Familiarity with server management technologies such as

IPMI, iDRAC, iLO and other out-of-band management tools . Understanding of storage technologies including

NVMe, SAN and NAS . Experience with firmware management, hardware diagnostics and vendor/RMA processes. Good understanding of data centre physical infrastructure, including

power, cooling and cabling . Experience with

GPU hardware, AI infrastructure or high-performance computing (HPC)

would be a significant advantage. Strong documentation skills and a structured, methodical approach to troubleshooting.

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