Machine Learning Engineer

John Hancock Life Insurance Company (U.S.A.) is hiring a Machine Learning Engineer to build production ML and data infrastructure for underwriting and analytics workflows.

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

• Master’s degree (or foreign equivalent) in Data Science, Information Studies, Information Science, Computer Science, Machine Learning, or a closely related field
• 3+ years of Python programming experience for backend systems, automation, or machine learning workloads
• 3+ years with SQL or No
  
  SQL databases, including PostgreSQL or MongoDB
  , for data modeling, querying, or pipeline integration
• 3+ years developing or deploying ML models using Py Torch or Tensor Flow
• 3+ years building or maintaining backend APIs or microservices using FastAPI or Flask
• 2+ years deploying ML workflows or backend services using AWS or Azure
• 2+ years using containerization and orchestration tools including Docker and Kubernetes
• 2+ years using Git Hub Actions or Team City for Continuous Integration/Continuous Deployment (CI/CD)
• 2+ years designing distributed or scalable systems, including microservices, load balancing, or distributed processing

• Python
• SQL
• No
  
  SQL
• PostgreSQL
• MongoDB
• Py Torch
• Tensor Flow
• FastAPI
• Flask
• AWS
• Azure
• Docker
• Kubernetes
• Git Hub Actions
• Team City

• Salary: $162,198 per year
• Expected range: $90,160.00 USD - $ USD

• Eligible employees may participate in incentive programs and earn incentive compensation tied to business and individual performance
• Health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage, adoption/surrogacy and wellness benefits, and employee/family assistance plans
• Retirement savings plans including pension/401(k) savings plans and a global share ownership plan with employer matching contributions
• Financial education and counseling resources
• Paid time off program in the U.S.: up to 11 paid holidays, 3 personal days, 150 hours of vacation, and 40 hours of sick time each year (or more where required by law), plus statutory leaves of absence

• Hybrid role based in Boston, MA (3 days in office, 2 days from home)