Hong Kong
Live, first seen by us 86 days agoWorking Arrangement HybridRead the full posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Build and maintain data pipelines and feature engineering workflows for Health AI models
Develop MLOps practices: experiment tracking, versioning, CI/CD, testing and monitoring
Build and operate model serving, APIs, batch inference and GenAI services
Implement RAG, agentic workflows, vector search and evaluation frameworks
Improve reliability, performance, cost and observability of Health AI platforms
Design, build, and maintain scalable data pipelines and feature engineering workflows
Develop robust MLOps practices across the model lifecycle
Build and operate reliable model serving capabilities, APIs, batch inference jobs, and GenAI services
Implement modern AI engineering patterns such as retrieval augmented generation, prompt orchestration, function calling, agentic workflows, vector search, and evaluation frameworks
Improve reliability, performance, cost efficiency, and observability of Health AI platforms
Proven experience 6 years+ designing and operating scalable data pipelines, feature engineering workflows, and model training pipelines for production AI/ML systems.
Hands-on experience building and scaling model serving capabilities, APIs, batch inference pipelines, and GenAI services on cloud platforms such as Azure, Databricks, Spark, and containerized deployment environments.
Practical knowledge of modern GenAI engineering patterns, including retrieval augmented generation, vector search, prompt orchestration, function calling, agentic workflows, and evaluation frameworks.
Experience improving platform reliability, performance, cost efficiency, and observability through logging, monitoring, alerting, model performance tracking, and continuous optimization.
Ability to translate Health AI use cases into secure, reusable, production-grade engineering patterns in partnership with data science, data engineering, IT, and business teams.
Strong communication, ownership, and mentoring skills, with the ability to guide engineering best practices and collaborate effectively across technical and non-technical stakeholders.
We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals.
In the employer’s words · Read in context
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 86
Up longer than most. Similar jobs usually come down between day 8 and day 76.
Well past Manulife Financial’s usual: its jobs come down by about day 27.
From 5,461 similar postings that came down, and 179 of Manulife Financial’s. Coming down is not always a hire.
36 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Hands-on experience building and scaling model serving capabilities, APIs, batch inference pipelines, and GenAI services on cloud platforms such as Azure, Databricks, Spark, and containerized deployment environments. - Advanced programming skills in Python and SQL, with practical experience in ML frameworks, data processing tools, orchestration pipelines, and GenAI engineering packages such as LangChain, LangGraph, ADK, or CrewAI. - Practical knowledge of modern GenAI engineering patterns, including retrieval augmented generation, vector search, prompt orchestration, function calling, agentic workflows, and evaluation frameworks.
- Strong MLOps expertise across the full model lifecycle, including experiment tracking, model versioning, CI/CD, automated testing, deployment automation, monitoring, and release governance. - Hands-on experience building and scaling model serving capabilities, APIs, batch inference pipelines, and GenAI services on cloud platforms such as Azure, Databricks, Spark, and containerized deployment environments. - Advanced programming skills in Python and SQL, with practical experience in ML frameworks, data processing tools, orchestration pipelines, and GenAI engineering packages such as LangChain, LangGraph, ADK, or CrewAI.
Complete your application on manulife.wd3.myworkdayjobs.com. The employer’s form will show what is required.
Already applied? Track this application
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
We are seeking a highly skilled Senior Machine Learning Engineer to join our Health AI Squad at Manulife Asia, based in Singapore / Hong Kong. This role will focus on building scalable, production-grade AI/ML and GenAI capabilities that advance Health AI across Asia. As part of the regional Health AI team, you will design, build, and operate robust data pipelines, model services, and GenAI platforms that turn complex health data into practical solutions, while applying modern machine learning and Generative AI patterns such as retrieval augmented generation, prompt engineering, function calling, and agentic workflows to help deliver Health AI at scale across multiple Asian markets.
Position Responsibilities:
Required Qualifications:
What motivates you?
About Manulife and John Hancock
Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit https://www.manulife.com/en/about/our-story.html.
Manulife is an Equal Opportunity Employer
At Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.
It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact hr@manulife.com.
Working Arrangement
Selected passages from the saved posting. Check the full description for conditions and exceptions.
No pay amount identified in the saved description.
Hong Kong
Working Arrangement Hybrid
This passage needs a closer read in the full description.