HPC & AI Systems Admin Intern (Hybrid)

Hewlett Packard Enterprise Company; Bloomington (IN); Hybrid; USD 4,822,000 - 5,648,000; Full time

Job summary

Hewlett Packard Enterprise Company is seeking an HPC AI Systems Administrator Intern to join the HPC and AI Data Center Administration team. The role emphasizes security visibility, monitoring, and automation in a Linux-based lab environment.

You will help build repeatable reports, document hardening practices, and create dashboards to track remediation work, gaining hands-on exposure to large-scale compute environments and observability workflows.

Qualifications

• Familiarity with Linux systems administration and working without a GUI.
• Currently enrolled in a degree program in cybersecurity, computer science, software engineering, information systems, computer engineering, network administration, or related technical field.
• Ability to use the Linux command line, navigate filesystems, edit config files, inspect services and logs, manage users/permissions, and troubleshoot without a GUI.

Responsibilities

• Validate inventory for HPC and AI lab systems.
• Review monitoring, logging, and vulnerability coverage across a heterogeneous fleet.
• Identify gaps in deployment, logging, and scans; build reports, dashboards, and checklists.
• Document hardening expectations and practical steps for lab systems.
• Collaborate with system admins to validate findings and prioritize follow-up work.
• Present project results and recommendations at internship end.

Skills

Linux command line

no GUI operation

written communication

learning willingness

Education

CS/CE/IS/engineering degree

Tools

SSH key management

Git/GitHub

Job description

Hewlett Packard Enterprise Company is seeking an HPC AI Systems Administrator Intern to join the HPC and AI Data Center Administration team. The role emphasizes security visibility, monitoring, and automation in a Linux-based lab environment.

You will help build repeatable reports, document hardening practices, and create dashboards to track remediation work, gaining hands-on exposure to large-scale compute environments and observability workflows.