AI Systems Infrastructure Engineer | Up to $7K

The Supreme HR Advisory Pte Ltd; Singapore; On-site; SGD 56,000 - 78,000; Full time

Job summary

The Supreme HR Advisory Pte Ltd seeks an AI Infrastructure Engineer to design, deploy and manage large multi‑GPU compute clusters in Singapore. You will optimize Linux systems, tune kernels, and automate with IaC to support distributed AI workloads.

You will work with Kubernetes, Slurm, Ray, and HPC schedulers; ensure low latency networking (RDMA/InfiniBand) and high‑IOPS storage; collaborate with AI/ML teams and maintain golden images and firmware updates.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or equivalent practical experience.
• 3–6+ years of hands-on experience in infrastructure engineering, HPC, DevOps, or cloud infrastructure.
• Relevant certifications (e.g., CKA/CKAD, NVIDIA, AWS/Azure/GCP) are a plus.
• Experience with multi-GPU compute clusters and AI/ML distributed workloads.

Responsibilities

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

Skills

Linux administration

Kernel tuning

Shell scripting

Bash

Python

GPU architectures

CUDA runtimes

Kubernetes

Slurm

Ray

RDMA

InfiniBand

PFC configurations

High IO storage

Education

Bachelor’s degree in CS/IT/Engineering

Tools

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

• 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 datapipelines.

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.

POH LI WEN REG NO: R25136683

THE SUPREMEHR ADVISORY PTE LTDEANO:14C7279