Hybrid ML Engineer: Scalable Data Pipelines

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

Benefits offered by this job

Health insurance

Dental insurance

Vision care

Disability insurance

Life insurance

AD&D insurance

Adoption benefits

Wellness benefits

401(k)/pension plan

Paid time off

Job summary

John Hancock Life Insurance Company (USA) is seeking a Machine Learning Engineer to build scalable data pipelines and ML/AI backends for underwriting analytics. You will collaborate with data scientists, underwriters, and engineers to translate business requirements into robust production systems.

The role demands a Master’s degree and strong Python, ML framework, and cloud/container experience, with production deployment, monitoring, and CI/CD expertise.

Qualifications

• Master’s degree in Data Science, Information Studies, Information Science, Computer Science, Machine Learning, or closely related field.
• 3 years of Python programming experience for backend systems, automation, or ML workloads.

Responsibilities

• Develop, build and maintain scalable data pipelines supporting underwriting, analytics, and ML 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.
• Support production releases and large‑scale batch processing of underwriting workflows.

Skills

Python

SQL/NoSQL

PyTorch/TensorFlow

FastAPI/Flask

AWS/Azure

Docker

Kubernetes

CI/CD

Microservices

Data pipelines

ML deployment

Education

Master's degree in Data Science / CS

Tools

PostgreSQL

MongoDB

Job description

John Hancock Life Insurance Company (USA) is seeking a Machine Learning Engineer to build scalable data pipelines and ML/AI backends for underwriting analytics. You will collaborate with data scientists, underwriters, and engineers to translate business requirements into robust production systems.

The role demands a Master’s degree and strong Python, ML framework, and cloud/container experience, with production deployment, monitoring, and CI/CD expertise.