Senior Machine Learning Engineer - Health AI

About the role

Manulife Asia is looking for a Senior Machine Learning Engineer to join its Health AI Squad, based in Singapore / Hong Kong. The role builds scalable, production-grade AI/ML and GenAI capabilities that advance Health AI across Asia, designing, building and operating data pipelines, model services and GenAI platforms that turn complex health data into practical solutions.

Key responsibilities

• Design, build and maintain scalable data pipelines and feature engineering workflows for Health AI model development, evaluation and production deployment.
• Develop MLOps practices across the model lifecycle, including experiment tracking, model versioning, CI/CD, automated testing, monitoring and governance-ready releases.
• Build and operate model serving, APIs, batch inference jobs and GenAI services that scale across use cases and markets.
• Partner with data scientists, data engineers, AI developers and IT teams to productionize solutions using approved cloud architecture, security standards and reusable patterns.
• Implement GenAI patterns such as retrieval augmented generation, prompt orchestration, function calling, agentic workflows, vector search and evaluation frameworks.
• Improve reliability, performance, cost efficiency and observability through logging, monitoring, alerting and continuous optimization.
• Create reusable templates, tools and engineering standards, and stay current with ML engineering, MLOps, cloud-native AI platforms and GenAI architecture.

Required profile

• Advanced degree in Computer Science, Machine Learning, Engineering, Data Science, Statistics or another quantitative field, with strong hands-on production ML engineering experience.
• 6+ years designing and operating scalable data pipelines, feature and model training pipelines for production AI/ML systems.
• Strong MLOps expertise and hands-on experience building model serving, APIs, batch inference and GenAI services on cloud platforms.
• Ability to turn Health AI use cases into secure, reusable engineering patterns with data science, data engineering, IT and business teams.
• Strong communication, ownership and mentoring skills.

Required skills

• Python and SQL; ML frameworks, data processing tools and orchestration pipelines.
• GenAI packages such as LangChain, LangGraph, ADK or CrewAI.
• Cloud platforms such as Azure and Databricks, Spark, and containerized deployments.
• Retrieval augmented generation, vector search, prompt orchestration, function calling and agentic workflows.

Working arrangement: hybrid.