Machine Learning Engineer

Experteer Overview In this role you will design and deploy production-grade ML solutions that create business value across Ventas’ enterprise. You will work at the intersection of software engineering and data science to build scalable ML systems and manage model lifecycles. You will partner with cross-functional teams to translate needs into technical solutions and ensure trustworthy, compliant deployments. This is a high-impact position in a fast-paced environment where you help enable secure, data-driven decisions at scale. Compensation / Benefits * Design, train, and deploy supervised and unsupervised ML models (regression, classification, clustering, anomaly detection) * Build and maintain end-to-end ML pipelines (data ingestion, feature engineering, training, evaluation, inference) * Collaborate with Data Science, Data Engineering, and business stakeholders to translate requirements into scalable solutions * Implement MLOps practices (CI/CD, model versioning, monitoring, retraining) * Optimize model performance, scalability, reliability, and cost in production * Integrate ML models into enterprise apps, APIs, and data platforms * Ensure data quality, model explainability, and adherence to security, governance, and compliance standards * Communicate ML concepts and results to technical and non-technical audiences Tasks * Bachelor’s degree in Computer Science, Data Science, Engineering, or equivalent experience * 5+ years of experience building and deploying ML models in production * Location: Chicago, IL area or willing to relocate * Willingness to blend remote and in-office work (3 days in office) * Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn) * Strong experience with AWS SageMaker for data prep, pipelines, and deployment * Experience with Git and modern software engineering practices * Familiarity with SQL (including T-SQL) and relational/geospatial databases * Experience with retrieval-augmented generation or generative AI is a plus * Understanding of Agile development and evolving environments * Must be legally authorized to work in the United States without sponsorship Key requirements * discretionary incentive compensation * medical, dental, vision benefits * retirement savings plan * paid time off * wellness benefits

help * Optimize model performance, scalability, reliability, and cost in production * Integrate ML models into enterprise apps, APIs, and data platforms * Ensure data quality, model explainability, and adherence to security, governance, and compliance standards * Communicate ML concepts and results to technical and non-technical audiences Tasks * Bachelor’s degree in Computer Science, Data Science, Engineering, or equivalent experience * 5+ years of experience building and deploying ML models in production * Location: Chicago, IL area or willing to relocate * Willingness to blend remote and in-office work (3 days in office) * Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn) * Strong experience with AWS SageMaker for data prep, pipelines, and deployment * Experience with Git and modern software engineering practices * Familiarity with SQL (including T-SQL) and relational/geospatial databases * Experience with retrieval-augmented generation or generative AI is 4 _ plus * Understanding of Agile development and evolving environments * Must be legally authorized to work in the United States without sponsorship Key requirements * discretionary incentive compensation * medical, dental, vision benefits * retirement savings plan * paid time off * wellness benefits