Machine Learning Engineer
Darwill
- Oak Brook, Illinois, United States
- Oak Brook, Illinois, United States
À propos
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 ML Engineering & MLOps
Partner closely with Data Scientists to support traditional ML model development, including feature engineering, 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 Deployment, Monitoring & Operations
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 GenAI (Secondary / Directional)
Contribute to GenAI initiatives as capacity allows Stay informed on emerging AI technologies and tooling (GenAI is not the primary focus of this role today.) Required Qualifications Experience
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 Technical Skills (Must-Have) Data Engineering & Platform
Apache Spark (PySpark, SparkSQL) Databricks (ETL pipelines, workflows, Delta Lake) Strong SQL skills (complex queries, joins, window functions, optimization) Experience building and maintaining scalable data pipelines Programming & Machine Learning
Python (pandas, numpy, scikit-learn; experience with XGBoost or LightGBM preferred) Feature engineering and data preparation for ML models Working knowledge of supervised learning models (classification, regression, ranking) MLOps & Production
Experience deploying ML models into production Model versioning and experiment tracking (e.g., MLflow or similar) Monitoring data quality and model performance in production Supporting retraining and validation workflows Cloud & Tooling
Experience with a major cloud platform (Databrick, AWS) Familiarity with workflow orchestration tools (Databricks Workflows or similar) Preferred Qualifications (Nice-to-Have)
Experience with propensity modeling, customer segmentation, or marketing analytics Exposure to CI/CD concepts for data and ML pipelines Experience with Docker or containerized deployments Exposure to GenAI, LLMs, or RAG-based systems Master's degree in Computer Science, Statistics, or a related field
Compétences linguistiques
- English
Avis aux utilisateurs
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