HPC High Performance Computing IT Infra Engineer

D L RESOURCES PTE LTD; Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

D L RESOURCES PTE LTD is seeking an HPC/Systems Administrator to support day-to-day operations of on-prem HPC clusters, including compute, storage, and high-speed networking. The role covers installation, patching, and maintenance of Linux/Unix systems, virtualization, and user access management.

You will monitor workloads, optimize performance, and assist with cluster scaling. Experience with Slurm/PBS/LSF, monitoring tools, and cloud exposure is valued.

Qualifications

• 1–3 years of hands-on Linux/Unix administration experience.
• Familiarity with HPC, distributed systems or parallel computing.
• Strong networking knowledge (TCP/IP, DNS, SSH, firewall).
• Experience with Slurm, PBS or LSF and batch processing workflows.
• Experience with monitoring/logging tools such as Nagios, Zabbix, Prometheus, Grafana, ELK Stack.

Responsibilities

• Support day-to-day operations of HPC clusters, compute nodes, storage, and networking infrastructure.
• Monitor system performance, workload execution, job scheduling, and resource utilization across distributed environments.
• Perform installation, configuration, patching, and maintenance of Linux/Unix OS (RHEL, CentOS, Ubuntu).
• Administer physical and virtualized server environments (x86, VMware/KVM).
• Support workload management systems and batch schedulers (Slurm, PBS, LSF) for resource allocation.
• Conduct system health checks, log analysis, troubleshooting, and incident management (root cause analysis).
• Manage user accounts, access control, and authentication (LDAP, AD integration).
• Assist in provisioning and config HPC environments, including software stack deployment and environment modules.
• Collaborate on cluster optimization, scaling, and performance tuning initiatives.
• Maintain system documentation, runbooks, and operational procedures.

Skills

Linux/Unix administration

Networking basics

Bash/Shell scripting

Python scripting

HPC/distributed systems

Job schedulers (Slurm/PBS/LSF)

Monitoring/logging tools

VMware / KVM virtualization

Cloud exposure (AWS)

LDAP / Active Directory knowledge

Tools

VMware

KVM

Slurm

PBS

LSF

Docker

Kubernetes

Nagios

Zabbix

Prometheus

Grafana

ELK Stack

Splunk

Job description

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 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

Project / Environment Tech Stack. (Mostly On-Prem)

The project environment is primarily on‑premise, with approximately 80% of the infrastructure hosted on Dell and servers, and approximately 20% involving AWS-based HPC/GPU server environments. This provides exposure to both traditional data centre infrastructure and cloud-based GPU/HPC workloads.

of:

80% On-Premise HPC Infrastructure

• Dell servers, Huawei servers, physical data centre infrastructure
• x86 server architecture, CPU-based compute infrastructure, bare-metal servers
• Virtualized server environments using VMware / KVM where applicable
• Linux/Unix-based systems including RHEL, CentOS, Ubuntu, AIX
• HPC cluster components across compute, storage, and networking layers
• High-performance storage / parallel file systems such as IBM Spectrum Scale (GPFS), Lustre, BeeGFS; with NAS / SAN / NFS exposure where applicable
• Cluster networking and connectivity including TCP/IP, DNS, SSH, firewall concepts, high-throughput Ethernet; InfiniBand / RDMA exposure preferred
• HPC workload scheduling and batch processing using Slurm, PBS, or LSF
• Monitoring and logging tools such as Nagios, Zabbix, Prometheus, Grafana, ELK Stack, or Splunk

20% AWS HPC / GPU-Related Environment

• AWS cloud infrastructure supporting HPC / GPU-related workloads
• AWS GPU server exposure, including NVIDIA GPU-based compute instances
• GPU computing environment exposure, including NVIDIA CUDA, NVIDIA drivers, GPU utilization, and GPU workload monitoring where applicable
• Cloud HPC workload support involving compute, storage, networking, and security configurations
• Exposure to AWS HPC services or related tools such as AWS ParallelCluster, AWS Batch, EC2 GPU instances, EBS / FSx / S3 storage, VPC, IAM, and security groups
• Container and DevOps exposure where applicable, including Docker, Kubernetes, and basic CI/CD or automation practices
• Hybrid HPC environment exposure involving on-premise infrastructure integrated with AWS-based compute or GPU resources