Engineering Lead - Production LLM & AI Systems

ASUS; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

AICS in Singapore is looking for an Engineering Manager to lead a team of Machine Learning Engineers building production-ready LLM applications, AI infrastructure, and clinical AI systems.

You will drive design, development, and deployment, establish best practices for AI development and MLOps, and work with AI Research, Product, and Software Engineering teams to translate research into production products.

Qualifications

• 8+ years of software engineering, machine learning engineering, or AI engineering experience.
• 3+ years leading technical engineering teams.

Responsibilities

• Lead and grow a high-performing Machine Learning Engineering team.
• Drive the design, development, and deployment of production LLM applications and AI systems.
• Build scalable AI engineering workflows covering model evaluation, experimentation, deployment, and continuous improvement.
• Lead the development of agentic AI capabilities, including multi-agent workflows, tool integration, memory, and orchestration.
• Establish engineering best practices for AI development, software quality, testing, and MLOps.
• Work closely with AI Research, Product, and Software Engineering teams to translate research into production products.
• Continuously evaluate emerging AI technologies and adopt new techniques that improve product quality and engineering productivity.

Skills

LLM development

Generative AI

Fine-tuning

Evaluation benchmarking

Retrieval systems

Agentic AI

Orchestration

Prompt engineering

Tool calling

PyTorch

Hugging Face

MLOps

Deployment optimization

Tools

PyTorch

Hugging Face

Job description

AICS in Singapore is looking for an Engineering Manager to lead a team of Machine Learning Engineers building production-ready LLM applications, AI infrastructure, and clinical AI systems.

You will drive design, development, and deployment, establish best practices for AI development and MLOps, and work with AI Research, Product, and Software Engineering teams to translate research into production products.