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.