AI Training Cluster Hardware Engineer

RUNSUN SERVICE PTE. LTD.

Singapore

On-site

SGD 120,000 - 180,000

Full time

14 days+

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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

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

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