AI Systems Infrastructure Engineer

OneAsia Network Limited; Hong Kong; On-site; HKD 600,000 - 900,000; Full time

Job summary

OneAsia Network Limited is seeking an analytical AI System Analyst to optimize and manage the infrastructure powering its AI capabilities. This role bridges AI Research teams and Data Center Operations to ensure resources support LLMs and high-performance computing.

You will drive hardware specs, capacity planning, MLOps integration with Kubernetes/Slurm, and storage optimization for high-throughput data processing. Expect vendor management and system reliability across large-scale training.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Information Systems, or a related field.
• 3+ years of experience in Data Center operations, Systems Analysis, or HPC.

Responsibilities

• Infrastructure Architecture: analyze hardware requirements for AI clusters (GPU, InfiniBand).
• Capacity & Performance Planning: forecast GPU, power and cooling needs; identify bottlenecks.
• MLOps Integration: optimize resource scheduling with Kubernetes or Slurm.
• Storage Optimization: design high-throughput storage for data ingestion.
• TCO & Vendor Management: perform TCO analysis and manage vendor relationships.
• Reliability Analysis: monitor AI systems and perform RCA on failures during large-scale training.

Skills

GPU architectures

PCIe/NVLink

Kubernetes

Docker

PyTorch

TensorFlow

RDMA/InfiniBand

Education

Bachelor’s or Master’s degree in CS/EE/IS

Tools

Kubernetes

Docker

Job description

OneAsia Network Limited is seeking an analytical AI System Analyst to optimize and manage the infrastructure powering its AI capabilities. This role bridges AI Research teams and Data Center Operations to ensure resources support LLMs and high-performance computing.

You will drive hardware specs, capacity planning, MLOps integration with Kubernetes/Slurm, and storage optimization for high-throughput data processing. Expect vendor management and system reliability across large-scale training.