MLOps Engineer - Data Pipelines & AI (Hybrid, Chicago)

Darwill; Chicago (IL); Hybrid; USD 115,000 - 180,000; Full time

Job summary

Darwill, a Chicago-area print and marketing tech firm, is seeking a mid-level Machine Learning Engineer (MLOps) to productionize ML models and build Databricks data pipelines powering analytics.

The role is hybrid in the Chicago area (Oak Brook / West Suburbs) with 1–2 days onsite per week. You’ll collaborate with Data Scientists, optimize pipelines, monitor models, and contribute to GenAI initiatives.

Qualifications

• 3–6 years of professional ML/data engineering experience.
• Experience in production environments with minimal supervision.
• Proven ability to translate models into production systems with data pipelines.

Responsibilities

• Design, build, and maintain ETL pipelines in Databricks using Spark and Delta Lake.
• Collaborate with Data Scientists on feature engineering, training, validation, and deployment.
• Productionize propensity, ranking, and segmentation models for large campaigns.
• Monitor data quality, model performance, and retraining workflows.
• Implement versioning, experiment tracking, and reproducibility standards.

Skills

Apache Spark

Databricks

SQL

Python (pandas, numpy, scikit-learn)

Feature engineering

Supervised learning

Education

Master’s degree in Computer Science or Statistics

Tools

MLflow

Databricks Workflows

Docker

CI/CD

AWS

Job description

Darwill, a Chicago-area print and marketing tech firm, is seeking a mid-level Machine Learning Engineer (MLOps) to productionize ML models and build Databricks data pipelines powering analytics.

The role is hybrid in the Chicago area (Oak Brook / West Suburbs) with 1–2 days onsite per week. You’ll collaborate with Data Scientists, optimize pipelines, monitor models, and contribute to GenAI initiatives.