UPMC Health Plan is seeking a skilled and motivated MLOps Engineer to join our AI Solutions team. In this role, you will be responsible for designing, building, and maintaining the infrastructure and tools that enable the deployment, monitoring, and scaling of machine learning models in production. You will work closely with data scientists, software engineers, and Cloud Engineering teams to streamline the ML lifecycle and ensure robust, secure, and efficient model operations.

Responsibilities:

Develop and maintain CI/CD pipelines for machine learning workflows, including model training, validation, deployment, and monitoring. Collaborate with data scientists to productionize ML models and ensure reproducibility and scalability.  Design and implement model versioning, model registry, and automated retraining strategies. Monitor model performance and data drift in production environments and implement alerting and rollback mechanisms. Optimize infrastructure for cost, performance, and reliability using cloud-native tools and services (e.g., AWS, Azure, GCP). Ensure compliance with data governance, security, and privacy standards throughout the ML lifecycle.  Automate data ingestion, feature engineering, and model evaluation processes. Contribute to the development of internal tools and frameworks to support experimentation and deployment. Document best practices and provide guidance to cross-functional teams on MLOps principles.