Hybrid ML Engineer: Scale ML Pipelines & Production Systems

Manulife; Boston (MA); Hybrid; USD 90,000 - 167,000; Full time

Job summary

John Hancock Life Insurance Company (USA) is hiring a Machine Learning Engineer to build scalable data pipelines, deploy ML models, and support underwriting analytics in a hybrid Boston office.

You will develop backend services, enable ML inference workflows, and collaborate with data scientists, underwriters, and engineers.

The role requires a Master’s degree and 3 years of Python experience, with SQL/NoSQL, PyTorch/TensorFlow, FastAPI/Flask, Docker, Kubernetes, and CI/CD.

Qualifications

• 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.
• 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.

Responsibilities

• 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.

Skills

Python

SQL/NoSQL

PyTorch

TensorFlow

Web APIs

AWS/Azure

Docker

Kubernetes

CI/CD

Microservices

Education

Master’s degree

Tools

FastAPI

Flask

Job description

John Hancock Life Insurance Company (USA) is hiring a Machine Learning Engineer to build scalable data pipelines, deploy ML models, and support underwriting analytics in a hybrid Boston office.

You will develop backend services, enable ML inference workflows, and collaborate with data scientists, underwriters, and engineers.

The role requires a Master’s degree and 3 years of Python experience, with SQL/NoSQL, PyTorch/TensorFlow, FastAPI/Flask, Docker, Kubernetes, and CI/CD.