Senior HPC Engineer-
Role/Job title
Senior HPC Engineer
Work Location
Stevenage, UK
Role type - Permanent/Fixed Term/Contracting
Contracting
Mode of working - Hybrid/office based
Hybrid
If Hybrid, how many days are required in office?
3 days
Number of positions
1
Unit
IS-LSHC-1-Life Sciences
Duration of assignment
6 - 12 months
Any other working conditions - travel/on call/shifts
None
To be published on job boards from below onwards
The Role
We are seeking an experienced Senior HPC Engineer to support and evolve enterprise High Performance Computing (HPC) platforms used for research, engineering, and computational workloads. The successful candidate will be responsible for administering and optimizing HPC infrastructure, with particular emphasis on Linux (RHEL), Slurm workload management, and Nvidia GPU-based computing environments. The role requires hands-on experience supporting both traditional HPC clusters and GPU-accelerated platforms, including Nvidia DGX/HGX systems.
Your responsibilities:
Administer, maintain, and troubleshoot production HPC environments.
Manage and support Slurm workload scheduling infrastructure.
Install, configure, patch, and support Red Hat Enterprise Linux (RHEL) systems.
Deploy, manage, and troubleshoot Nvidia GPU platforms, including DGX/HGX infrastructure.
Install, maintain, and upgrade Nvidia drivers, CUDA toolkits, and GPU software stacks.
Monitor cluster performance, capacity, availability, and resource utilization.
Support researchers, engineers, and technical users running compute-intensive workloads.
Diagnose and resolve hardware, operating system, storage, network, and application issues.
Work with vendors and internal stakeholders to deliver HPC infrastructure improvements.
Develop and maintain automation, operational procedures, and technical documentation.
Your Profile
Essential skills/knowledge/experience:
5+ years experience supporting High Performance Computing (HPC) environments.
Strong administration experience with Red Hat Enterprise Linux (RHEL 7/8/9).
Hands-on administration of Slurm Workload Manager in production environments.
Experience managing HPC clusters, compute nodes, and scheduling infrastructure.
Practical experience supporting Nvidia GPU-based platforms.
Hands-on experience with Nvidia DGX and/or HGX systems.
Experience installing, configuring, upgrading, and troubleshooting Nvidia GPU drivers.
Strong working knowledge of CUDA and GPU-accelerated workloads.
Experience troubleshooting Linux, hardware, storage, and networking issues within HPC environments.
Ability to work directly with engineers, researchers, and technical stakeholders.
Strong problem-solving, communication, and documentation skills.
Desirable skills/knowledge/experience:
Experience with HPC storage technologies such as Lustre or GPFS.
Knowledge of InfiniBand networking.
Experience supporting AI/ML or GPU-accelerated workloads.
Familiarity with OpenMPI, MPICH, or parallel computing frameworks.
Experience with automation tools such as Ansible.
Knowledge of container technologies including Docker or Apptainer/Singularity.
Experience with HPC hardware life cycle management and cluster expansion projects.
Exposure to cloud-based HPC environments.
Relevant certifications such as RHCSA, RHCE, or Nvidia certifications.
Senior HPC Engineer
Work Location
Stevenage, UK
Role type - Permanent/Fixed Term/Contracting
Contracting
Mode of working - Hybrid/office based
Hybrid
If Hybrid, how many days are required in office?
3 days
Number of positions
1
Unit
IS-LSHC-1-Life Sciences
Duration of assignment
6 - 12 months
Any other working conditions - travel/on call/shifts
None
To be published on job boards from below onwards
The Role
We are seeking an experienced Senior HPC Engineer to support and evolve enterprise High Performance Computing (HPC) platforms used for research, engineering, and computational workloads. The successful candidate will be responsible for administering and optimizing HPC infrastructure, with particular emphasis on Linux (RHEL), Slurm workload management, and Nvidia GPU-based computing environments. The role requires hands-on experience supporting both traditional HPC clusters and GPU-accelerated platforms, including Nvidia DGX/HGX systems.
Your responsibilities:
Administer, maintain, and troubleshoot production HPC environments.
Manage and support Slurm workload scheduling infrastructure.
Install, configure, patch, and support Red Hat Enterprise Linux (RHEL) systems.
Deploy, manage, and troubleshoot Nvidia GPU platforms, including DGX/HGX infrastructure.
Install, maintain, and upgrade Nvidia drivers, CUDA toolkits, and GPU software stacks.
Monitor cluster performance, capacity, availability, and resource utilization.
Support researchers, engineers, and technical users running compute-intensive workloads.
Diagnose and resolve hardware, operating system, storage, network, and application issues.
Work with vendors and internal stakeholders to deliver HPC infrastructure improvements.
Develop and maintain automation, operational procedures, and technical documentation.
Your Profile
Essential skills/knowledge/experience:
5+ years experience supporting High Performance Computing (HPC) environments.
Strong administration experience with Red Hat Enterprise Linux (RHEL 7/8/9).
Hands-on administration of Slurm Workload Manager in production environments.
Experience managing HPC clusters, compute nodes, and scheduling infrastructure.
Practical experience supporting Nvidia GPU-based platforms.
Hands-on experience with Nvidia DGX and/or HGX systems.
Experience installing, configuring, upgrading, and troubleshooting Nvidia GPU drivers.
Strong working knowledge of CUDA and GPU-accelerated workloads.
Experience troubleshooting Linux, hardware, storage, and networking issues within HPC environments.
Ability to work directly with engineers, researchers, and technical stakeholders.
Strong problem-solving, communication, and documentation skills.
Desirable skills/knowledge/experience:
Experience with HPC storage technologies such as Lustre or GPFS.
Knowledge of InfiniBand networking.
Experience supporting AI/ML or GPU-accelerated workloads.
Familiarity with OpenMPI, MPICH, or parallel computing frameworks.
Experience with automation tools such as Ansible.
Knowledge of container technologies including Docker or Apptainer/Singularity.
Experience with HPC hardware life cycle management and cluster expansion projects.
Exposure to cloud-based HPC environments.
Relevant certifications such as RHCSA, RHCE, or Nvidia certifications.