Remote HPC Site Reliability Engineer (Systems Analyst)

Hewlett Packard Enterprise; United States; On-site; USD 110,000 - 150,000; Full time

Job summary

Hewlett Packard Enterprise is seeking a Systems Analyst with Site Reliability Engineer expertise to support Oak Ridge National Lab in security-focused HPC environments. This role combines on-site duties at ORNL with remote-friendly collaboration, focusing on deployment, maintenance, and optimization of large-scale computing software infrastructure to ensure system reliability.

You will work with researchers and engineers to implement automation, monitor performance, and troubleshoot complex

Qualifications

• Experience with SLURM-based HPC systems (user and admin).
• Proficient in Linux, Python, and Bash scripting.
• Familiar with C++/Fortran HPC development, GPUs, MPI.
• Knowledge of build processes, compiler configurations, libraries, and dependencies.
• Experience in log analysis and performance troubleshooting.
• Strong written and verbal communication skills.
• Familiarity with HPC trends, architectures, and optimization strategies.

Responsibilities

• Maintain and optimize compute infrastructure across HPC systems.
• Deploy, test, and validate HPC clusters.
• Troubleshoot node failures via OS internals and logs.
• Maintenance and performance tuning for large HPC environments.
• Collaborate with researchers and engineers to manage tickets.
• Document complex issues and liaise with internal teams.
• Develop automation tools, scripts, and monitoring solutions.
• Stay current with HPC tech including ROCm, Cray MPI/OpenMP.

Skills

SLURM HPC systems

Linux

Python

Bash

C++/Fortran HPC

MPI

GPU/ROCm

Education

BS/MS in Computer Science or Computer Engineering

Job description

Hewlett Packard Enterprise is seeking a Systems Analyst with Site Reliability Engineer expertise to support Oak Ridge National Lab in security-focused HPC environments. This role combines on-site duties at ORNL with remote-friendly collaboration, focusing on deployment, maintenance, and optimization of large-scale computing software infrastructure to ensure system reliability.

You will work with researchers and engineers to implement automation, monitor performance, and troubleshoot complex