{"schemaVersion":"jobsearcher.job.v1","id":"8e257e182a0fe3476f1e8fdb","url":"https://jobsearcher.com/jobs/8e257e182a0fe3476f1e8fdb","canonicalUrl":"https://jobsearcher.com/jobs/8e257e182a0fe3476f1e8fdb","title":"Machine Learning Engineer","description":"MACHINE LEARNING ENGINEER (MLOPS / DATA ENGINEERING)\nOverview\nDarwill is a nationally recognized print and marketing communications firm based in the west suburbs of Chicago. As a premier provider of complex, data-driven marketing solutions, we help CMOs and marketing leaders drive measurable performance through advanced analytics, automation, and AI-powered insights.\nWe are seeking a Machine Learning Engineer (MLOps) to support the productionization of traditional machine learning models (e.g., propensity and segmentation models) while also building and maintaining the core data pipelines on Databricks that power our analytics and modeling platforms.\nThis role is intentionally scoped for a mid-level engineer: someone with enough experience to work independently and make sound engineering decisions, but who is still hands-on, execution-focused, and eager to grow. This is not an entry-level position, and it is not a principal or architect-level role..\n\nLocation\nChicago, IL area (Oak Brook / West Suburbs)\nHybrid work model with 1–2 days onsite per week required\n\nReports To\nVP of Data Engineering & Data Science\n\nResponsibilities / Essential Functions\nData Engineering & Platform Foundations\nDesign, build, and maintain ETL pipelines in Databricks using Spark and Delta Lake\nIndependently implement data transformations, joins, and aggregations across large, multi-source datasets\nBuild and maintain data validation and quality checks to ensure reliability of downstream analytics and ML workflows\nOptimize Databricks jobs for performance, scalability, and cost efficiency\nWrite and maintain clear technical documentation for data pipelines and tables\nML Engineering & MLOps\nPartner closely with Data Scientists to support traditional ML model development, including feature engineering, training, validation, and deployment\nProductionize propensity, ranking, and segmentation models used in large-scale marketing campaigns\nBuild and maintain repeatable ML pipelines for training, batch scoring, and inference\nImplement model versioning, experiment tracking, and reproducibility standards\nSupport model performance monitoring, drift detection, and retraining cycles\nDeployment, Monitoring & Operations\nDeploy data pipelines and ML workflows into production environments serving millions of records\nImplement monitoring and alerting for data and ML pipelines\nSupport A/B testing and model performance evaluation in partnership with Data Science\nTroubleshoot production issues independently and collaborate effectively when escalation is needed\nGenAI (Secondary / Directional)\nContribute to GenAI initiatives as capacity allows\nStay informed on emerging AI technologies and tooling\n(GenAI is not the primary focus of this role today.)\n\nRequired Qualifications\nExperience\n3–6 years of professional experience in machine learning engineering, data engineering, or a closely related role\nExperience working in production environments with minimal day-to-day supervision\nDemonstrated ability to collaborate effectively with Data Scientists and translate models into production systems\nTechnical Skills (Must-Have)\nData Engineering & Platform\nApache Spark (PySpark, SparkSQL)\nDatabricks (ETL pipelines, workflows, Delta Lake)\nStrong SQL skills (complex queries, joins, window functions, optimization)\nExperience building and maintaining scalable data pipelines\nProgramming & Machine Learning\nPython (pandas, numpy, scikit-learn; experience with XGBoost or LightGBM preferred)\nFeature engineering and data preparation for ML models\nWorking knowledge of supervised learning models (classification, regression, ranking)\nMLOps & Production\nExperience deploying ML models into production\nModel versioning and experiment tracking (e.g., MLflow or similar)\nMonitoring data quality and model performance in production\nSupporting retraining and validation workflows\nCloud & Tooling\nExperience with a major cloud platform (Databrick, AWS)\nFamiliarity with workflow orchestration tools (Databricks Workflows or similar)\n\nPreferred Qualifications (Nice-to-Have)\nExperience with propensity modeling, customer segmentation, or marketing analytics\nExposure to CI/CD concepts for data and ML pipelines\nExperience with Docker or containerized deployments\nExposure to GenAI, LLMs, or RAG-based systems\nMaster’s degree in Computer Science, Statistics, or a related field","company":"Darwill","rawCompany":"darwill","city":"Oakbrook Terrace","state":"IL","isRemote":false,"isActive":false,"createdAt":"2026-04-09T09:14:50.861Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer","description":"MACHINE LEARNING ENGINEER (MLOPS / DATA ENGINEERING)\nOverview\nDarwill is a nationally recognized print and marketing communications firm based in the west suburbs of Chicago. As a premier provider of complex, data-driven marketing solutions, we help CMOs and marketing leaders drive measurable performance through advanced analytics, automation, and AI-powered insights.\nWe are seeking a Machine Learning Engineer (MLOps) to support the productionization of traditional machine learning models (e.g., propensity and segmentation models) while also building and maintaining the core data pipelines on Databricks that power our analytics and modeling platforms.\nThis role is intentionally scoped for a mid-level engineer: someone with enough experience to work independently and make sound engineering decisions, but who is still hands-on, execution-focused, and eager to grow. This is not an entry-level position, and it is not a principal or architect-level role..\n\nLocation\nChicago, IL area (Oak Brook / West Suburbs)\nHybrid work model with 1–2 days onsite per week required\n\nReports To\nVP of Data Engineering & Data Science\n\nResponsibilities / Essential Functions\nData Engineering & Platform Foundations\nDesign, build, and maintain ETL pipelines in Databricks using Spark and Delta Lake\nIndependently implement data transformations, joins, and aggregations across large, multi-source datasets\nBuild and maintain data validation and quality checks to ensure reliability of downstream analytics and ML workflows\nOptimize Databricks jobs for performance, scalability, and cost efficiency\nWrite and maintain clear technical documentation for data pipelines and tables\nML Engineering & MLOps\nPartner closely with Data Scientists to support traditional ML model development, including feature engineering, training, validation, and deployment\nProductionize propensity, ranking, and segmentation models used in large-scale marketing campaigns\nBuild and maintain repeatable ML pipelines for training, batch scoring, and inference\nImplement model versioning, experiment tracking, and reproducibility standards\nSupport model performance monitoring, drift detection, and retraining cycles\nDeployment, Monitoring & Operations\nDeploy data pipelines and ML workflows into production environments serving millions of records\nImplement monitoring and alerting for data and ML pipelines\nSupport A/B testing and model performance evaluation in partnership with Data Science\nTroubleshoot production issues independently and collaborate effectively when escalation is needed\nGenAI (Secondary / Directional)\nContribute to GenAI initiatives as capacity allows\nStay informed on emerging AI technologies and tooling\n(GenAI is not the primary focus of this role today.)\n\nRequired Qualifications\nExperience\n3–6 years of professional experience in machine learning engineering, data engineering, or a closely related role\nExperience working in production environments with minimal day-to-day supervision\nDemonstrated ability to collaborate effectively with Data Scientists and translate models into production systems\nTechnical Skills (Must-Have)\nData Engineering & Platform\nApache Spark (PySpark, SparkSQL)\nDatabricks (ETL pipelines, workflows, Delta Lake)\nStrong SQL skills (complex queries, joins, window functions, optimization)\nExperience building and maintaining scalable data pipelines\nProgramming & Machine Learning\nPython (pandas, numpy, scikit-learn; experience with XGBoost or LightGBM preferred)\nFeature engineering and data preparation for ML models\nWorking knowledge of supervised learning models (classification, regression, ranking)\nMLOps & Production\nExperience deploying ML models into production\nModel versioning and experiment tracking (e.g., MLflow or similar)\nMonitoring data quality and model performance in production\nSupporting retraining and validation workflows\nCloud & Tooling\nExperience with a major cloud platform (Databrick, AWS)\nFamiliarity with workflow orchestration tools (Databricks Workflows or similar)\n\nPreferred Qualifications (Nice-to-Have)\nExperience with propensity modeling, customer segmentation, or marketing analytics\nExposure to CI/CD concepts for data and ML pipelines\nExperience with Docker or containerized deployments\nExposure to GenAI, LLMs, or RAG-based systems\nMaster’s degree in Computer Science, Statistics, or a related field","datePosted":"2026-04-09T09:14:50.861Z","dateModified":"2026-04-09T09:14:50.861Z","hiringOrganization":{"@type":"Organization","name":"Darwill","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Oakbrook Terrace","addressRegion":"IL","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"8e257e182a0fe3476f1e8fdb"},"url":"https://jobsearcher.com/jobs/8e257e182a0fe3476f1e8fdb"}}