IT & Software

HPC Support Engineer

Hays

London · Greater London · United Kingdom

Overview

In this role you will support and enhance the institution's high-performance computing environment, including HPC and GPU clusters, research storage, high-speed networking and hybrid cloud infrastructure. You will administer Linux-based clusters, manage scientific software stacks and help researchers maximise HPC resources. You will automate deployment and monitoring using Python, Bash, Ansible, Docker, Kubernetes and CI/CD tools, while collaborating with researchers and technical teams. This is your chance to contribute to cutting-edge computational research and AI-driven projects at a prestigious, research-led university in London.

Responsibilities
  • Administer and support HPC clusters, GPU systems and specialist research hardware
  • Manage workload scheduling with Slurm or OpenPBS
  • Maintain scientific software, compilers and libraries using Spack or EasyBuild
  • Automate the lifecycle of compute and GPU nodes
  • Troubleshoot complex Linux, storage, networking and performance issues
  • Support containerised and cloud-based research workloads
  • Help researchers optimise applications for parallel computing and GPU acceleration
  • Deliver technical guidance, documentation and training
Key requirements
  • Advanced Linux cluster administration experience
  • Experience with HPC schedulers such as Slurm or OpenPBS
  • Knowledge of CUDA or OpenCL
  • Strong scripting and automation skills using Python, Bash or Ansible
  • Experience with Docker, Kubernetes, Git and CI/CD practices
  • Knowledge of monitoring and observability tools such as Grafana, ELK Stack or Splunk
  • Experience using HPC software build frameworks such as Spack or EasyBuild
  • Knowledge of scientific software stacks, compilers and libraries
  • Experience managing large-scale storage and file systems
  • The ability to work directly with researchers and translate technical requirements into practical solutions
  • Experience with cloud-based HPC, infrastructure-as-code tools, research computing environments or higher education would be advantageous
  • collaboration
  • clear communication with researchers
  • problem-solving
  • Advanced Linux cluster administration
  • HPC schedulers: Slurm or OpenPBS
  • CUDA or OpenCL

Reference: WJ-747_31001623

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