Machine Learning Engineer
Core
Transform machine learning models and AI solutions into reliable, scalable production systems to improve decision-making and automate operational processes.
Role type
Senior Machine Learning Engineer (MLOps & Production Deployment)
Builds
Production-ready ML services, APIs, document intelligence systems, and real-time decisioning platforms.
Domain
Financial services (lending, credit risk, collections, fraud)
Deliverable
production ML models
Required skills
Python development, production ML deployment, SQL, data engineering, CI/CD, containerisation, model monitoring, MLOps tooling, document processing/OCR, REST API development, Git, automated testing, cloud deployments, model evaluation and optimisation, event-driven architectures.
Preferred skills
Experience in financial services, Snowflake/Snowpark/dbt, Streamlit, champion-challenger testing, model explainability.
Technologies
Python, SQL, Snowflake, Snowpark, dbt, Git, Streamlit, MLOps platforms, OCR technologies, cloud platforms.
Responsibilities
Develop, deploy, and maintain ML/AI solutions in production; design and enhance document intelligence systems; build classification, forecasting, and optimisation solutions; transform prototypes into scalable applications; 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