Machine learning Engineer
Core
Build scalable and reliable machine learning systems for document intelligence, information extraction, and operational efficiency in a FinTech environment.
Role type
Machine Learning Engineer (Production & MLOps)
Builds
Scalable ML systems, document intelligence solutions, and real-time scoring APIs
Domain
Financial Technology (FinTech), Document Processing, AI
Required skills
Python, SQL, Snowflake/Snowpark, dbt, XGBoost/LightGBM, REST APIs, Docker, CI/CD, MLOps, Git, automated testing
Preferred skills
MLOps platforms, experiment tracking, workflow orchestration, model monitoring, document processing/OCR, semi-structured data extraction
Technologies
Snowflake, Snowpark, dbt, XGBoost, LightGBM, Docker, Streamlit
Responsibilities
Deploy ML and AI solutions into scalable production environments; Develop and maintain document intelligence and information extraction systems using OCR and AI-assisted workflows; Convert analytical models and prototypes into robust, modular Python applications and services; Build batch, real-time, and event-driven scoring solutions and APIs; Implement MLOps best practices including CI/CD, testing, version control, monitoring, and orchestration; Monitor model performance, model drift, system reliability, and infrastructure costs.
Seniority
Mid-to-Senior, hands-on IC