AI Engineer - Up to $7K - 0310

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

Job summary

The Supremehr Advisory Pte Ltd is hiring an AI Infrastructure Engineer to design, deploy, and operate high-density GPU compute clusters for AI training and inference. You will optimize GPU data paths, monitor performance, and collaborate with AI/ML teams on distributed workloads.

You will implement container orchestration and HPC schedulers (Kubernetes, Slurm, Ray) with IaC practices, ensuring scalable, low-latency infrastructure and robust disaster recovery in a fast-paced environment.

Qualifications

• Bachelor's degree in Computer Science, IT, Computer Engineering or equivalent practical experience.
• 3–6+ years hands-on infra/HPC/DevOps or cloud infrastructure experience.
• Certifications such as CKA/CKAD or cloud architect certificates are a plus.

Responsibilities

• Architect, configure, and maintain high-density multi-GPU compute clusters (e.g. NVIDIA HGX/DGX).
• Implement and manage container orchestration platforms optimized for AI/ML workloads.
• Monitor GPU health, telemetry, utilization, and thermals; reduce idle compute time.
• Design and optimize low-latency networks and parallel storage for AI data pipelines.
• Build automated deployment pipelines using Terraform, Ansible, Helm, or Pulumi.
• Lead incident response, RCA, and disaster recovery for mission-critical AI environments.

Skills

Linux systems administration

Shell scripting

HPC/DevOps

Infrastructure monitoring

Education

Bachelor's degree in CS/IT/CE or equivalent

Tools

Kubernetes

Slurm

Ray

NVIDIA CUDA

RoCE/InfiniBand

Lustre/Ceph

Terraform

Ansible

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).

Education & Experience

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.

POH LI WEN REG NO: R25136683

THE SUPREMEHR ADVISORY PTE LTD EA NO: 14C7279