AI Systems Infrastructure Engineer - Up to $7K - 0310

THE SUPREME HR ADVISORY PTE. LTD.; Singapore; On-site; SGD 56,000 - 78,000; Full time

Job summary

The Supreme HR Advisory Pte. Ltd. is seeking an AI Infrastructure Engineer to design and operate large GPU-accelerated compute clusters and optimize AI/ML workflows within a demanding data-center environment.

You will implement container orchestration with Kubernetes and Slurm, tune Linux systems, monitor NVIDIA GPUs, and build automated pipelines with Terraform and Ansible. A strong background in HPC, networking, and fast storage is essential.

Qualifications

• Bachelor's Degree in Computer Science, Information Technology, Computer Engineering, or equivalent practical experience.
• 3-6+ years hands-on experience in infrastructure engineering, HPC, DevOps, or cloud infrastructure.
• Deep expertise in Linux systems administration, kernel tuning, and shell scripting.
• Strong understanding of GPU hardware architectures, CUDA runtimes, PCIe/NVLink.
• Certifications (CKA/CKAD, NVIDIA, AWS/Azure/GCP) are a plus.

Responsibilities

• Architect, configure, and maintain high-density multi-GPU compute clusters (NVIDIA HGX/DGX).
• Implement and manage container orchestration platforms optimized for AI/ML distributed workloads.
• Monitor GPU health, telemetry, utilization, and thermals; minimize idle compute time.
• Design and optimize low-latency networks and storage for AI data pipelines.
• Automate deployment pipelines with Terraform/Ansible; maintain golden images.
• Lead incident response and RCA for mission-critical AI environments.

Skills

Linux administration

Kernel tuning

Shell scripting

GPU architectures

CUDA

PCIe/NVLink

Kubernetes

Slurm

Ray

RDMA

InfiniBand

PFC

Lustre

Ceph

GPFS

Terraform

Ansible

Kernel parameters

Education

Bachelor's degree in Computer Science, Information Technology, Computer Engineering, or equivalent practical experience

Tools

Kubernetes

Slurm

Ray

Terraform

Ansible

Helm

Pulumi

Job description

AI Infrastructure Engineer

5 days, Mon - Fri 8.30am to 5.30pm

Salary: $5,000 to $7,000

Location: Kaki Bukit

Key Skills & Requirements

• Operating Systems: Deep expertise in Linux systems administration, kernel tuning, and shell scripting (Bash/Python).
• Accelerated Compute: Strong understanding of GPU hardware architectures, CUDA runtimes, and PCIe/NVLink topologies.
• Orchestration & Workload Scheduling: Hands-on experience with Kubernetes (GPU operator, device plugins) and/or HPC schedulers (Slurm, Run:ai, Ray).
• High-Speed Networking: Proven experience with RDMA (RoCE v2 /InfiniBand), PFC (Priority Flow Control), and ECN configurations.
• Storage Systems: Familiarity with high-IOPS, low-latency shared storage architectures for AI datasets and model checkpoints.
• Automation: Proficiency in Infrastructure as Code (Terraform) and configuration management (Ansible).
• Bachelor's Degree in Computer Science, Information Technology, Computer Engineering, or equivalent practical experience.
• 3-6+ years of hands-on experience in infrastructure engineering, high-performance computing (HPC), DevOps, or cloud infrastructure.
• Relevant certifications are a plus (e.g., CKA/CKAD, NVIDIA Certified Associate/Professional, AWS/Azure/GCP Solutions Architect).

Job scopes

Compute & Cluster Management

• Architect, configure, and maintain high-density multi-GPU compute clusters (e.g. NVIDIA HGX/DGX architectures).
• Implement and manage container orchestration platforms (Kubernetes, Slurm, or Ray) optimized for AI/ML distributed workloads.
• Monitor GPU health, telemetry, utilization, and thermals; minimize idle compute time and prevent single-node bottlenecks.

High-Performance Networking & Storage

• Design and optimize low-latency, lossless network fabrics supporting distributed training (InfiniBand, RoCE v2, NVLink, spine-leaf topologies).
• Configure and scale high-throughput parallel file systems and object storage (e.g. Lustre, GPFS/IBM Spectrum Scale, Ceph, MinIO, NVMe-oF) to feed high-speed data pipelines.

Automation & Infrastructure as Code (IaC)

• Build and manage automated deployment pipelines using Terraform, Ansible, Helm, or Pulumi.
• Maintain standard golden images, Linux OS tuning (kernel parameters, NUMA node binding, GPU drivers, CUDA/cuDNN libraries), and firmware updates.

Operations, Observability & Performance

• Set up end-to-end monitoring, alerting, and metrics dashboards (Prometheus, Grafana, DCGM exporter, NVIDIA System Management Interface).
• Partner with AI/ML engineering teams to diagnose network bottlenecks, NCCL communication latency, and I/O wait states during distributed training jobs.
• Lead incident response, root-cause analysis (RCA), and disaster recovery plans for mission-critical AI environments.