Machine Learning Engineer
Core
Transform machine learning models and prototypes into reliable, scalable production systems that improve decision-making and automate operational processes.
Role type
Senior Machine Learning Engineer (MLOps & Production Deployment)
Builds
Production-ready ML solutions, APIs, pipelines, and document intelligence systems for a digital business.
Domain
Financial services (lending, credit risk, collections, fraud) / Machine Learning / MLOps
Deliverable
production ML models
Required skills
Python development, production ML deployment, SQL, data engineering, CI/CD, containerization, cloud deployments, model monitoring, REST API development, data pipelines, event-driven architectures, MLOps tooling, modern data platforms (Snowflake, Snowpark, dbt), OCR/document processing, model explainability, champion-challenger testing.
Preferred skills
Experience in financial services environments, real-time decisioning platforms, Streamlit, model evaluation and optimization.
Technologies
Python, SQL, Snowflake, Snowpark, dbt, Git, Docker/Kubernetes (implied by containerisation), MLOps platforms, Streamlit.
Responsibilities
Develop and maintain ML/AI solutions in production; design document intelligence and information extraction systems; build classification, forecasting, and optimization solutions; transform prototypes into scalable applications; develop APIs and reusable ML services; implement CI/CD and automated testing; integrate ML into customer journeys; monitor model performance and data quality; investigate production issues; define success metrics and evaluate business impact.
Seniority
Senior, hands-on IC