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Job description
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.
Responsibilities
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
Requirements
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 NoSQL databases, including PostgreSQL or MongoDB , for data modeling, querying, or pipeline integration
3+ years developing or deploying ML models using PyTorch or TensorFlow
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 GitHub Actions or TeamCity for Continuous Integration/Continuous Deployment (CI/CD)
2+ years designing distributed or scalable systems, including microservices, load balancing, or distributed processing
Technologies
Python
SQL
NoSQL
PostgreSQL
MongoDB
PyTorch
TensorFlow
FastAPI
Flask
AWS
Azure
Docker
Kubernetes
GitHub Actions
TeamCity
Compensation
Salary: $162,198 per year
Expected range: $90,160.00 USD - $167,440.00 USD
Benefits
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
Work Arrangement
Hybrid role based in Boston, MA (3 days in office, 2 days from home)
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Worksite address
boston, MA, 02298, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.