Senior Machine Learning Engineer

About the role

We are looking for a Senior Machine Learning Engineer to join the Health AI Squad at Manulife Asia. Based in Singapore (with coverage of Hong Kong), you will build scalable, production‑grade AI/ML and Generative AI solutions that power health‑focused services across multiple Asian markets.

Key responsibilities

• Design, develop and maintain robust data pipelines and feature‑engineering workflows for health‑AI model training and deployment.
• Implement end‑to‑end MLOps practices, including experiment tracking, model versioning, CI/CD, automated testing, monitoring and governance‑ready releases.
• Build and operate reliable model serving APIs, batch inference jobs and GenAI services that can scale across diverse use cases.
• Collaborate with data scientists, data engineers, AI developers and IT teams to productionise solutions using approved cloud architecture and security standards.
• Apply modern AI patterns such as retrieval‑augmented generation, prompt orchestration, function calling, agentic workflows, vector search and evaluation frameworks.
• Enhance platform reliability, performance, cost efficiency and observability through logging, alerting and continuous optimisation.
• Create reusable templates, tools and engineering standards to accelerate delivery of production‑grade health AI capabilities.

Required profile

• Advanced degree (MSc/PhD) in Computer Science, Machine Learning, Data Science, Statistics or a related quantitative field.
• 6+ years of hands‑on experience designing and operating scalable data pipelines, feature‑engineering workflows and model training pipelines for production AI/ML systems.
• Deep expertise in MLOps across the full model lifecycle, including experiment tracking, model versioning, CI/CD, testing, deployment automation, monitoring and release governance.
• Proven ability to build and scale model serving, APIs, batch inference and GenAI services on cloud platforms such as Azure, Databricks and Spark, using containerised environments.
• Strong programming skills in Python and familiarity with modern AI engineering patterns.

Required skills

• Python
• Azure
• Databricks
• Apache Spark
• Containerisation (Docker/Kubernetes)
• MLOps tools (experiment tracking, CI/CD, model versioning)
• API development and batch inference
• Generative AI techniques (retrieval‑augmented generation, prompt engineering, function calling, agentic workflows, vector search)