Machine Learning Engineer
Core
Design, build, deploy, and maintain machine learning and AI solutions in production environments, transforming data science models into scalable applications for document processing, information extraction, automation, forecasting, and classification.
Role type
Machine Learning Engineer (Production/Deployment)
Builds
Production-ready ML models, APIs, pipelines, and automated scoring solutions
Domain
Financial services / Lending / Credit risk / Fraud / Regulated industry
Deliverable
production ML models
Required skills
Python, SQL, REST API development, Git, Machine Learning model development and optimization, CI/CD practices, Automated testing
Preferred skills
MLOps tooling, Snowflake/Snowpark/dbt, Containerization, XGBoost/LightGBM, OCR/Document intelligence
Technologies
Python, SQL, Snowflake, Snowpark, dbt, XGBoost, LightGBM, Git
Responsibilities
Design and deploy ML solutions, develop intelligent systems for document processing and forecasting, transform prototypes into production apps, build APIs and pipelines, implement CI/CD and monitoring, monitor model performance and drift, integrate ML into business systems, define success metrics
Seniority
Mid-Senior, hands-on IC