GPU AI Infrastructure Engineer II

Proxima Beta Pte. Limited; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Tencent Overseas IT is seeking a skilled systems engineer in Singapore to design, develop, and deliver GPU/AI infrastructure platforms and tools for large-scale AI workloads. You will build core capabilities for GPU resource management, workload scheduling, distributed training, and inference across clusters.

You will collaborate with algorithm and business teams to tackle AI workload engineering challenges, optimize cluster performance, and improve infrastructure efficiency using Python/Go/C++,

Qualifications

• Strong software engineering in Python, Go, or C++.
• Solid Linux, Docker, and Kubernetes fundamentals.
• Familiarity with GPU technologies such as CUDA, NCCL, and RDMA.
• Experience with distributed systems or distributed computing.
• Experience with AI coding/AI agents or AI-assisted development.
• Experience in LLM training, inference, or GPU cluster infrastructure is a plus.

Responsibilities

• Design, develop, and deliver GPU/AI infrastructure platforms and tools.
• Build core capabilities for GPU resource management, workload scheduling, distributed training, and inference.
• Develop and improve the engineering infrastructure around mainstream AI frameworks and runtimes for LLM workloads.
• Optimize GPU cluster performance, stability, and resource utilization.
• Work closely with algorithm and business teams to solve AI workload engineering challenges and improve infrastructure efficiency.

Skills

Python

Go

C++

Linux

Docker

Kubernetes

CUDA

NCCL

RDMA

Distributed systems

AI Coding / AI Agents

LLM training / inference

Tools

Docker

Kubernetes

CUDA

NCCL

RDMA

Job description

Tencent Overseas IT is seeking a skilled systems engineer in Singapore to design, develop, and deliver GPU/AI infrastructure platforms and tools for large-scale AI workloads. You will build core capabilities for GPU resource management, workload scheduling, distributed training, and inference across clusters.

You will collaborate with algorithm and business teams to tackle AI workload engineering challenges, optimize cluster performance, and improve infrastructure efficiency using Python/Go/C++,