Join AgileEngine, an award-winning software development company ranked among the leaders in application development and AI/ML. We're an Inc. 5000 company with a people-first culture that's earned us multiple Best Place to Work awards. Job Overview As our ML Ops Engineer, you'll work on building and maintaining scalable ML infrastructure on Databricks, leveraging Unity Catalog and feature stores to support model development and deployment. You'll design and implement frameworks for detecting data and model drift, ensuring continuous monitoring and high reliability of ML models in production. Develop model calibration frameworks and establish versioning practices to maintain transparency and reproducibility across the ML lifecycle. Design and optimize reinforcement learning (RL) orchestration pipelines for real-time execution in low-latency environments. Create automated frameworks for training, retraining, and validating ML models, enabling efficient experimentation and deployment. Implement CI/CD best practices to streamline the deployment and monitoring of ML models, integrating with Databricks workflows and Git-based version control systems. Work closely with ML Scientists to ship, deploy, and maintain models. Build tools for model performance monitoring, operational analytics, and drift mitigation, ensuring reliable operation in production environments.