MLOps Engineer for Databricks Propensity & Segmentation

Darwill, Inc.; Oakbrook Terrace (IL); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Darwill, Inc. is seeking a mid-level Machine Learning Engineer (MLOps) to productionize traditional ML models and to build and maintain core data pipelines on Databricks.

The role emphasizes hands-on execution with growth potential, located in the Chicago area with hybrid work (1–2 days onsite weekly). The candidate will collaborate with Data Scientists on feature engineering, training, validation, and deployment, and will work on propensity, ranking, and segmentation models for large marketing

Qualifications

• 3–6 years of professional experience in machine learning engineering, data engineering, or a closely related role.
• Experience working in production environments with minimal day-to-day supervision.
• Demonstrated ability to collaborate effectively with Data Scientists and translate models into production systems.

Responsibilities

• 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 with Data Scientists to support model development, training, validation, and deployment.
• 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.

Skills

Python

Feature engineering

Supervised learning

Production ML deployment

MLOps

Collaboration with Data Scientists

Education

Master’s degree (preferred)

Tools

Apache Spark

Databricks

SQL

MLflow

Docker

AWS

Databricks Workflows

Job description

Darwill, Inc. is seeking a mid-level Machine Learning Engineer (MLOps) to productionize traditional ML models and to build and maintain core data pipelines on Databricks.

The role emphasizes hands-on execution with growth potential, located in the Chicago area with hybrid work (1–2 days onsite weekly). The candidate will collaborate with Data Scientists on feature engineering, training, validation, and deployment, and will work on propensity, ranking, and segmentation models for large marketing