Senior AI Infrastructure Engineer - High Performance Compute

Newbridge; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Confidential in Singapore is building a GREENFIELD GPU cloud to deploy thousands of GPUs for AI inference and real-time rendering. This role lets you architect environments from the ground up, with a modern stack featuring H100, A100, and L40S, no legacy constraints.

You will own the design, deployment, and operation of large-scale GPU infrastructure, optimize performance, and drive automation for provisioning, monitoring, and multi-tenancy, while supporting AI/ML customers with demanding

Qualifications

• 4+ years in GPU systems, HPC, or AI infrastructure.
• Hands-on with NVIDIA GPUs, CUDA, driver stack, GPU operator, and Kubernetes.
• Strong Linux and networking fundamentals, with high-performance fabrics.
• Bonus: experience with GPU cloud platforms (CoreWeave/Lambda/Vultr style).

Responsibilities

• Architect, deploy, and operate large-scale GPU infrastructure - bare metal + orchestration
• Optimize GPU performance, drivers, CUDA, networking (InfiniBand, RoCE), and virtualization
• Build automation for GPU provisioning, monitoring, and multi-tenancy
• Support AI/ML customers with high-performance GPU workloads

Skills

GPU Systems

HPC

AI Infrastructure

CUDA

Kubernetes

Linux

Networking

InfiniBand

RoCE

Multi-tenancy

Automation

Tools

NVIDIA CUDA Toolkit

Job description

Confidential | AI & High-Performance Compute Platform. Our client is now powering the next wave of AI inference and real-time rendering workloads on their own GPU cloud.

Why This Role Is Exciting:

This is a GREENFIELD GPU cloud build. You will not just maintain GPUs, you will architect how thousands of GPUs are deployed, virtualized, and delivered as a service for AI customers. High demand, cutting-edge stack (H100, A100, L40S), zero legacy.

What You Will Own:

• Architect, deploy, and operate large-scale GPU infrastructure - bare metal + orchestration
• Optimize GPU performance, drivers, CUDA, networking (InfiniBand, RoCE), and virtualization
• Build automation for GPU provisioning, monitoring, and multi-tenancy
• Support AI / ML customers with high-performance GPU workloads

Who You Are:

• 4+ years with GPU Systems / HPC / AI Infrastructure
• Hands-on with NVIDIA GPUs, CUDA, driver stack, GPU operator, Kubernetes
• Strong Linux and networking fundamentals, experience with high-performance fabrics
• Bonus: Experience with GPU cloud providers, CoreWeave / Lambda / Vultr style platforms