Machine Learning Engineer

Darwill is seeking a Machine Learning Engineer (MLOps) to support the productionization of traditional machine learning models and build and maintain core data pipelines on Databricks.

Requirements

• Design, build, and maintain ETL pipelines in Databricks using Spark and Delta Lake
• Independently implement data transformations, joins, and aggregations across large, multi-source datasets
• Build and maintain data validation and quality checks to ensure reliability of downstream analytics and ML workflows
• Optimize Databricks jobs for performance, scalability, and cost efficiency
• Write and maintain clear technical documentation for data pipelines and tables
• Partner closely with Data Scientists to support traditional ML model development
• Productionize propensity, ranking, and segmentation models used in large-scale marketing campaigns
• Build and maintain repeatable ML pipelines for training, batch scoring, and inference
• Implement model versioning, experiment tracking, and reproducibility standards
• Support model performance monitoring, drift detection, and retraining cycles
• Deploy data pipelines and ML workflows into production environments serving millions of records
• Implement monitoring and alerting for data and ML pipelines
• Support A/B testing and model performance evaluation in partnership with Data Science
• Troubleshoot production issues independently and collaborate effectively when escalation is needed
• Contribute to GenAI initiatives as capacity allows