GPU Cloud & AI Infrastructure Lead

zy future international pte. ltd.; Singapore; On-site; SGD 167,000 - 223,000; Full time

Job summary

zy future international pte. ltd. seeks a Technical Manager to lead architecture, development, deployment and operation of a GPU Cloud and AI infrastructure platform in Singapore.

You will guide GPU servers, AI computing clusters, cloud-native platforms and multi-tenant workloads with a focus on stability and scalability. The role requires hands-on experience with GPU clusters, HPC/infrastructure, Linux, Docker, Kubernetes, and cloud-native stacks.

Qualifications

• Bachelor’s degree in CS/EC/related discipline or equivalent experience.
• At least 7 years in cloud computing, HPC, AI infra or data center environments.
• 3+ years hands-on building or operating GPU clusters and AI platforms.
• Strong Linux, Docker, Kubernetes, Helm and cloud-native tech knowledge.
• Experience with GPU drivers, acceleration libraries and AI server stacks.
• Fluent English; Mandarin proficiency required for coordination.

Responsibilities

• Lead GPU infrastructure architecture for servers and AI clusters.
• Plan and operate GPU Cloud platforms and resource pools with scheduling.
• Support AI workloads including training, fine-tuning and inference.
• Establish monitoring, SLA management and capacity planning.
• Coordinate with sales, product, and vendors for scalable services.
• Oversee project delivery, risk management and documentation.

Skills

GPU Clusters

AI infrastructure

Kubernetes

Slurm

InfiniBand / RoCE

RDMA

NVIDIA GPU Driver management

Linux system administration

Education

Bachelor's degree in Computer Science or related

Tools

Docker

Kubernetes

Helm

NVIDIA GPU Operator

Job description

zy future international pte. ltd. seeks a Technical Manager to lead architecture, development, deployment and operation of a GPU Cloud and AI infrastructure platform in Singapore.

You will guide GPU servers, AI computing clusters, cloud-native platforms and multi-tenant workloads with a focus on stability and scalability. The role requires hands-on experience with GPU clusters, HPC/infrastructure, Linux, Docker, Kubernetes, and cloud-native stacks.