Build and run production machine learning and data systems in a hybrid Boston role.

Develop, build, and maintain scalable data pipelines for underwriting, analytics, and machine learning systems
Create 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 environments
Perform root-cause analysis for data, model, and pipeline issues, and implement corrective solutions
Partner with data scientists, underwriters, and engineering teams to turn 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 of experience with 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 and Continuous Deployment (CI/CD)
2 years of experience designing distributed or scalable systems, including microservices, load balancing, or distributed processing

Incentive programs with incentive compensation tied to business and individual performance (eligible employees)
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 (U.S.): up to 11 paid holidays, 3 personal days, 150 hours of vacation, and 40 hours of sick time (or more where required by law) each year, plus statutory leaves of absence

Machine Learning Engineer

Job Description