Hardware Engineer

RUNSUN SERVICE PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

RUNSUN SERVICE PTE. LTD. seeks an experienced AI Hardware Engineer to support design, deployment, validation, and troubleshooting of AI training clusters, GPU servers, networking, and storage infrastructure.

The ideal candidate will possess strong expertise in server hardware, GPU platforms, high-speed networking, and data center infrastructure to support large-scale AI/HPC environments. The role requires hands-on Linux, scripting, and on-site operational capabilities, with readiness for on-call

Qualifications

• Bachelor's degree or above in Computer Engineering, Electrical Engineering, Telecommunications, or related fields.
• Strong knowledge of x86 server architecture.
• Experience with NVIDIA GPU products (H100, H200, B200, B300).
• Familiar with CUDA, NCCL, NVLink, NVSwitch and GPU Direct RDMA.
• Strong Linux administration skills (Ubuntu, Rocky Linux) and scripting (Shell, Python).

Responsibilities

• Deploy, validate, and maintain AI GPU servers.
• Analyze system logs, BMC logs, and hardware alerts.
• Participate in AI/HPC cluster deployment and validation.
• Configure and maintain high-speed networking and distributed storage.
• Develop automation scripts for hardware health checks and deployment.
• Participate in on-call rotation and occasional business trips.

Skills

Linux administration

Python scripting

Shell/Bash scripting

x86 server architecture

NVIDIA GPU platforms

NVIDIA Grace CPU

Networking (TCP/IP, InfiniBand, RoCE)

BMC/IPMI management

On-call readiness

Education

Bachelor's degree in Computer Engineering, Electrical Engineering, Telecommunications, or related fields

Tools

HGX

DGX

GB200 NVL72

GB300 NVL72

CUDA

NCCL

GPU Direct RDMA

Job description

We are seeking an experienced AI Hardware Engineer to support the design, deployment, validation, and troubleshooting of AI training clusters, GPU servers, networking, and storage infrastructure. The ideal candidate should have strong expertise in server hardware, GPU platforms, high-speed networking, and data center infrastructure to support large-scale AI/HPC environments.

Key Responsibilities

AI Server Hardware Management

• Deploy, validate, and maintain AI GPU servers;
• Perform hardware diagnostics and component replacement;
• Analyze system logs, BMC logs, and hardware alerts;
• Manage server hardware lifecycle.

GPU Platform Support

• Deploy and validate NVIDIA GPU platforms;
• Troubleshoot GPU-related;
• Perform GPU benchmarking and stress testing;
• Support CUDA, NCCL, and GPU fabric troubleshooting.

AI Cluster Deployment & Validation

• Participate in AI/HPC cluster deployment;
• Execute cluster hardware qualification testing;
• Produce validation reports and documentation.

Network & Storage Support

• Configure and maintain high-speed networking:
• Support distributed storage systems:
• Assist with performance analysis and troubleshooting.

Automation & Tool Development

• Develop automation scripts for:

  Hardware health checks

  Cluster validation

  Deployment automation

  Log collection

• Build tools for testing and operations.

• Good communication, teamwork, and ownership mindset.
• Willing to participate in on-call rotation, maintenance windows, and emergency incident response, willing to accept short-term business trips.

Required Qualifications

Bachelor's degree or above in Computer Engineering, Electrical Engineering, Telecommunications, or related fields.

Hardware

• Strong knowledge of x86 server architecture;
• Familiar with Intel, AMD, and NVIDIA Grace CPU platforms;
• Experience with:
• HGX
• DGX
• GB200 NVL72
• GB300 NVL72
• Knowledge of BMC/IPMI management.

GPU & AI Platform

• Experience with NVIDIA GPU products H100, H200, B200, B300
  
• Familiar with: CUDA ,NCCL ,NV Link ,NV Switch and GPU Direct RDMA

Linux

• Strong Linux administration skills (Ubuntu, Rocky Linux);
• Proficient in: Shell ,Python , Bash
• Capable of independent troubleshooting.

Networking

Strong understanding of: TCP/IP , VLAN , BGP ,OSPF ,RDMA , InfiniBand and RoCE

Preferred Qualities

• Experience operating AI training clusters; Kubernetes experience; Slurm administration
• PXE deployment experience; GPU Fabric Manager expertise;
• Experience with hyperscale AI datacenter deployments.