Machine Learning Engineer
Core
Transform machine learning models, analytics assets, and AI solutions into reliable, scalable production systems to improve decision-making and automate operational processes.
Role type
Senior Machine Learning Engineer (Production/MLOps)
Builds
Production-ready ML solutions, APIs, pipelines, and document intelligence systems for a digital business.
Domain
Financial services (lending, credit risk, collections, fraud)
Deliverable
production ML models
Required skills
Python, SQL, machine learning frameworks, MLOps tooling, containerisation, CI/CD, REST API development, data pipelines, event-driven architectures, model monitoring, model evaluation, OCR/document processing, Snowflake/Snowpark/dbt, Git, automated testing
Preferred skills
Experience in financial services, real-time decisioning platforms, model explainability, champion-challenger testing, Streamlit, cloud-based deployments
Technologies
Python, SQL, Snowflake, Snowpark, dbt, Git, Streamlit, MLOps platforms
Responsibilities
Develop, deploy, and maintain ML/AI solutions in production; Design and enhance document intelligence and information extraction systems; Build solutions for classification, forecasting, optimisation, and pattern recognition; Transform prototypes into scalable applications; Develop APIs, pipelines, and reusable ML services; Implement CI/CD, automated testing, and containerisation; Integrate ML solutions into customer journeys; Monitor model performance, data quality, and prediction drift; Investigate production issues and optimise reliability; Define success metrics and evaluate business impact.
Seniority
Senior, hands-on IC