Principal Machine Learning Engineer
Core
End-to-end machine learning lifecycle ownership including data pipeline development, feature engineering, modeling, and deployment to predict risk for individual insureds and portfolios.
Role type
Principal Machine Learning Engineer (Risk & Insurance)
Builds
Production ML models and lightweight data pipelines for risk prediction and product improvement
Domain
Insurance / Risk Management / Machine Learning
Deliverable
production ML models
Required skills
Machine learning, Python, dbt, feature engineering, model deployment, monitoring, event-driven architecture, data pipeline design, risk evaluation, business impact analysis
Preferred skills
Actuarial experience, risk aggregation, computer vision, image analysis, team leadership, end-to-end deployment ownership
Technologies
AWS, Kafka, Django, FastAPI, Postgres, GitHub Actions, dbt Cloud
Responsibilities
Design, build, deploy, evaluate, and monitor ML models and datasets; Build lightweight data pipelines and dbt tables; Explore and implement ML applications to improve product outcomes; Write clean, maintainable code; Provide metrics on model quality and performance; Identify trends in large datasets; Shape ML strategy and architecture