Senior ML Engineer: GenAI & Multi-Node AI Architect

1100 Micron SemiAsiaOP Pte Ltd; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

Micron Technology in Singapore seeks a Senior Machine Learning Engineer (MTS) to architect and deploy large-scale models, including GenAI and autonomous AI Agents, across multi-node GPUs and optimized hardware.

You will optimize training throughput, build distributed data pipelines, integrate with cloud data warehousing, and collaborate with cross-functional teams to accelerate AI-driven manufacturing workflows.

Proficiency with PyTorch, PEFT (LoRA/QLoRA), LangChain, and CI/CD is essential.

Qualifications

• Technical Degree required.
• Computer Science or Statistics background desirable.
• Deep understanding of GPU architecture and distributed training.
• Experience with DDP, FSDP, and model parallelism.
• Proficiency in fine-tuning LLMs and optimizing inference engines.
• Experience with GenAI applications and AI Agents.

Responsibilities

• Architect and execute large-scale model training and fine-tuning on multi-node, multi-GPU clusters.
• Optimize training throughput and memory with distributed strategies and mixed precision.
• Design and develop autonomous AI Agents for multi-step workflows.
• Implement Agentic frameworks to orchestrate LLMs with internal APIs and tools.
• Profile and debug GPU bottlenecks to maximize hardware utilization.
• Build data and solution pipelines feeding ML models and GenAI apps.

Skills

GPU architecture

DDP

PEFT LoRA/QLoRA

LangChain

LangGraph

LlamaIndex

AutoGen

PyTorch

TensorRT-LLM

CI/CD

Education

Technical Degree

Computer Science or Statistics background

Tools

LangChain

LangGraph

LlamaIndex

AutoGen

PyTorch

CI/CD tools (Jenkins, Docker, Kubernetes)

Job description

Micron Technology in Singapore seeks a Senior Machine Learning Engineer (MTS) to architect and deploy large-scale models, including GenAI and autonomous AI Agents, across multi-node GPUs and optimized hardware.

You will optimize training throughput, build distributed data pipelines, integrate with cloud data warehousing, and collaborate with cross-functional teams to accelerate AI-driven manufacturing workflows.

Proficiency with PyTorch, PEFT (LoRA/QLoRA), LangChain, and CI/CD is essential.