Senior Machine Learning / MLOps Engineer

Our client is seeking a Senior Machine Learning / MLOps Engineer to help productionize and enhance an existing machine learning decisioning model within Azure Databricks. This individual will take ownership of transitioning an XGBoost-based model into a scalable production environment while building the pipelines, monitoring, CI/CD processes, and governance required to support long-term operations. The ideal candidate has a blend of hands-on machine learning expertise and MLOps experience, with the ability to develop, tune, deploy, monitor, and improve ML models throughout the full lifecycle. This is not a pure infrastructure or DevOps role. Candidates must have strong experience building and working directly with machine learning models in production.

• 5+ years of ML Engineering, MLOps, or Data Science experience

• Strong Python and SQL skills

• Experience building, training, and deploying ML models into production

• Hands-on experience with Azure Databricks, MLflow, and XGBoost (or similar frameworks)

• Experience with model monitoring, versioning, CI/CD, and automated testing

• Experience with Docker and cloud-based environments

Ability to work across the full ML lifecycle (development through deployment and retraining - Databricks Model Serving

• Unity Catalog

• Delta Lake

• Databricks Feature Engineering capabilities

• Microsoft Azure platform experience

• SHAP or other model explainability tools

• Kubernetes / AKS

• REST API development and integration

• Real-time model serving experience

• Insurance, claims, fraud, risk, or financial services industry experience

Experience working on decisioning or predictive analytics models