Machine Learning Engineer

Ventas, Inc. is seeking a Machine Learning Engineer to design, build, deploy, and maintain production-grade machine learning solutions across the enterprise. This hybrid role in Chicago, IL emphasizes scalable ML systems, model lifecycle management (MLOps), and integration with enterprise platforms.

Responsibilities

• Design, develop, train, and deploy machine learning models using supervised and unsupervised techniques, including regression, classification, clustering, and anomaly detection.
• Build and maintain end-to-end ML pipelines, covering data ingestion, feature engineering, training, evaluation, and inference.
• Collaborate with Data Science, Data Engineering, and business stakeholders to translate requirements into scalable technical solutions.
• Apply MLOps best practices, including CI/CD, model versioning, monitoring, and retraining strategies.
• Improve model performance, scalability, reliability, and cost efficiency for production deployments.
• Integrate machine learning models into enterprise applications, APIs, and data platforms.
• Support data quality efforts and model explainability while ensuring security, governance, and compliance standards are met.
• Present complex machine learning concepts and outcomes clearly to both technical and non-technical stakeholders.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Engineering, or equivalent experience.
• 5+ years of experience building and deploying machine learning models in production environments.
• Must be located in the Chicago, IL surrounding area or willing to relocate for the duration of employment.
• Willingness to work in a blended environment with 3 days in office, transitioning between remote work and in-office operations.
• Proficiency in Python and experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Strong experience using AWS SageMaker for data preparation, pipelines, and model deployment.
• Experience with Git and modern software engineering best practices.
• Familiarity with SQL, including T-SQL, and experience working with relational and geospatial databases.
• Experience with retrieval-augmented generation or generative AI solutions is a plus.
• Understanding of Agile development practices and comfort working in evolving, ambiguous environments.
• Legally authorized to work in the United States without employer sponsorship now or in the future.

Technology Stack

Python, TensorFlow, PyTorch, Scikit-learn, AWS SageMaker, Git, SQL, T-SQL.

Compensation

USD 135,000 - 175,000 per year.

Benefits

• Discretionary incentive compensation
• Comprehensive benefits package
• Medical
• Dental
• Vision
• Retirement savings
• Paid time off
• Other wellness benefits under applicable plan terms