AI Compute Architect: High-Performance Systems Lead

Beijing Foreign Enterprise Management Consultants Co.,Ltd.; Singapore; On-site; SGD 150,000 - 260,000; Full time

Job summary

Huawei in Singapore is seeking an AI Computing Architecture Researcher to design and optimize AI computing architectures and platforms for LLM, AIGC, distributed AI workloads. You will drive performance and scalability across hardware accelerators and software stacks.

The role requires a strong background in high-performance AI systems, fluency in C/C++, Python, and modern ML frameworks, plus experience with GPU/NPU programming and AI model optimization.

Qualifications

• Advanced degree in CS/EE; PhD preferred.
• Strong background in high-performance AI systems.
• Experience with AI model optimization (quantization, pruning, sparsity).
• Proficient low-level programming for performance (C/C++).

Responsibilities

• Design and optimize AI computing architectures and platforms for LLM, AIGC, distributed AI, and intelligent agent workloads.
• Develop software components interfacing with GPUs/NPUs and AI chips.
• Improve performance and efficiency of distributed computing and parallel processing.
• Collaborate with AI researchers to enhance platform performance for complex AI workloads.
• Design and implement tools for deployment, monitoring, and orchestration of AI workloads and agent systems.
• Integrate new AI models and algorithms into the computing architecture while ensuring scalability.
• Conduct profiling and benchmarking to achieve high throughput and low latency.

Skills

C/C++

Python

Parallel programming

Multi-agent coordination

Education

Master's or PhD in CS/EE

Tools

CUDA

Triton

cuTile

Docker

Kubernetes

PyTorch

TensorFlow

Job description

Huawei in Singapore is seeking an AI Computing Architecture Researcher to design and optimize AI computing architectures and platforms for LLM, AIGC, distributed AI workloads. You will drive performance and scalability across hardware accelerators and software stacks.

The role requires a strong background in high-performance AI systems, fluency in C/C++, Python, and modern ML frameworks, plus experience with GPU/NPU programming and AI model optimization.