Staff Machine Learning Engineer
Core
Own the infrastructure that gets ML models from development into product and marketing workflows, including deployment pipelines, feature stores, and monitoring systems.
Role type
Staff Machine Learning Engineer (MLOps & Infrastructure)
Builds
Deployment pipelines, feature stores, monitoring systems, retraining infrastructure, and data pipelines for product and marketing use cases.
Domain
Insurtech / Fintech
Deliverable
production ML models
Required skills
Real-time production ML model deployment, Python engineering, CI/CD, SQL, feature stores, workflow orchestration (Airflow), Docker, cloud infrastructure, supervised learning, Bayesian models, causal inference, marketing measurement (attribution, media mix), dbt, data warehouse tooling
Preferred skills
Experience in insurtech/fintech, ability to mentor, bridging data science and engineering
Technologies
AWS SageMaker, Airflow, Docker, dbt, SQL
Responsibilities
Own deployment and production lifecycle of models for coverage recommenders, user-to-channel routing, and agent assignment; Build and maintain feature pipelines for real-time inference; Implement automated monitoring for data drift and model degradation; Develop CI/CD pipelines and retraining infrastructure; Deploy and operationalize marketing models for attribution and media mix; Build reliable data pipelines for marketing inputs; Own model health monitoring and dependency management.
Seniority
Staff, hands-on IC with mentorship
