IT Infrastructure Engineer - HPC High Performance Computing
Summary
IT Infrastructure Engineer supporting HPC clusters (compute, storage, networking) for the Research & Education sector. Key tasks include Linux system administration (RHEL, Ubuntu), managing job schedulers like Slurm or PBS, and scripting with Bash or Python for automation.
Client: Research & Education Sector
Key Responsibilities
Support day-to-day operations of HPC clusters, including compute nodes, storage systems, and high-speed networking infrastructure
Monitor system performance, workload execution, job scheduling, and resource utilization across distributed environments
* Perform installation, configuration, patching, and maintenance of Linux/Unix operating systems (RHEL, CentOS, Ubuntu)
* Administer physical and virtualized server environments (x86 architecture, VMware/KVM)
* Support workload management systems and job schedulers (Slurm, PBS, LSF) for batch processing and resource allocation
* Conduct system health checks, log analysis, troubleshooting, and incident management (root cause analysis)
* Manage user accounts, access control, and authentication systems (LDAP, Active Directory integration)
* Assist in provisioning and configuration of HPC environments, including software stack deployment and environment modules
* Collaborate with senior engineers on cluster optimization, scaling, and performance tuning initiatives
* Maintain system documentation, operational procedures, and runbooks
Required Skills & Experience
1–3 years of experience in system administration, infrastructure support, or IT operations
Hands-on experience with Linux/Unix systems administration and command-line environments
* Basic exposure to HPC, distributed systems, or parallel computing environments
* Strong understanding of networking fundamentals (TCP/IP, DNS, SSH, firewall concepts)
* Knowledge of storage technologies (NAS, SAN, distributed/parallel file systems – basic awareness)
* Scripting and automation using Bash/Shell and/or Python
* Familiarity with monitoring and logging tools (e.g., Nagios, Zabbix, Prometheus, Grafana, ELK Stack)
* Strong troubleshooting, analytical thinking, and incident resolution skills
Preferred Skills
Exposure to GPU computing environments (NVIDIA GPUs, CUDA – basic awareness)
Familiarity with cloud platforms and HPC workloads on cloud (AWS, Azure)
* Awareness of container technologies (Docker) and basic DevOps practices
What the ideal candidate should have:
(A) Required / Basic Exposure:
Understanding of HPC cluster architecture, including compute nodes, storage systems and networking components.
Basic exposure to HPC job schedulers (Slurm, PBS or LSF).
Familiarity with Linux-based HPC environments and system administration.
Understanding of HPC workload monitoring, resource utilisation and troubleshooting.
Basic knowledge of enterprise storage, filesystems and networking.
(B) Preferred / Good to Have:
Exposure to parallel filesystems (GPFS, Lustre or BeeGFS).
Familiarity with InfiniBand, RDMA or high-speed cluster networking.
Exposure to GPU-based HPC environments (NVIDIA GPU/CUDA).
Experience supporting HPC workload optimisation or performance monitoring.
Exposure to HPC cluster deployment, provisioning or configuration