Artificial intelligence and machine learning have become integral to everyday tools, leading to the rapid growth of the ML Engineer role. However, model development presents challenges due to its isolation from traditional software development practices, necessitating the integration of DevOps and Security to meet MLOps needs. JFrog introduces ML Model Management, allowing organizations to manage proprietary and third-party models using their existing JFrog infrastructure, specifically Artifactory and Xray, to ensure the security and compliance of ML models. This integration facilitates automation, governance, and the extension of secure software supply chains to ML models, while also providing visibility and integrity through a unified management platform. In a practical example, JFrog's tools were used to detect an imposter at a company event by leveraging zero-shot object detection models, showcasing the platform's capabilities in integrating machine learning into existing workflows.