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# Machine Learning Engineer

- **Company:** Manulife
- **Location:** Boston, MA, United States
- **Experience:** Experienced
- **Salary:** $90,160.0 - $167,440.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Microsoft Azure, Batch Processing, Continuous Delivery, Continuous Integration, Distributed Computing Environment, Github, Information Sciences, Python (Programming Language), PostgreSQL, Machine Learning, MongoDB, NoSQL, Tensorflow, SQL Databases, Load Balancing, Data Ingestion, Pytorch, Flask (Web Framework), Backend, Fastapi, Containerization, Information Technology, Enterprise Integration, Machine Learning Operations, Teamcity, Data Pipelines, Docker, Microservices
- **Published:** August 25, 2026
- **Apply:** https://manulife.wd3.myworkdayjobs.com/MFCJH_Jobs/job/Boston-Massachusetts/Machine-Learning-Engineer_JR26081375

## About the Role

Master's degree or foreign equivalent in Data Science, Information Studies, Information Science, Computer Science, Machine Learning, or a closely related field and 3 years of Python programming experience for backend systems, automation, or machine learning workloads.

Experience must include the following, which may be gained concurrently:

 * 3 years of experience using SQL or NoSQL databases including PostgreSQL or MongoDB for data modeling, querying, or pipeline integration.
 * 3 years of experience developing or deploying machine learning models using PyTorch or TensorFlow.
 * 3 years of experience building or maintaining backend APIs or microservices using FastAPI or Flask.
 * 2 years of experience deploying ML workflows or backend services using AWS or Azure.
 * 2 years of experience using containerization and orchestration tools including Docker and Kubernetes.
 * 2 years of experience using GitHub Actions or TeamCity for Continuous Integration/ Continuous Deployment (CI/CD).
 * 2 years of experience designing distributed or scalable systems including microservices, load balancing or distributed processing.

## Description

* Develop, build and maintain scalable data pipelines supporting underwriting, analytics, and machine learning systems;
 * Develop and deploy backend services and microservices to support data ingestion, retrieval, and ML inference workflows;
 * Deploy, monitor, and maintain machine learning pipelines and backend services in production environments;
 * Conduct root-cause analysis of data, model, and pipeline issues and implement corrective solutions;
 * Collaborate with data scientists, underwriters, and engineering teams to translate business requirements into technical solutions; and
 * Support production releases and large-scale batch processing of underwriting workflows.


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