As an ML Ops and Automation Engineer, bridge the gap between machine learning development and production deployment. Design, implement, and maintain automated pipelines for model training, deployment, monitoring, and scaling. Collaborate with cross-functional teams to streamline the ML lifecycle and drive innovation in machine learning infrastructure. Key responsibilities include designing and implementing ML pipelines, infrastructure orchestration, model versioning and experiment tracking, CI/CD, monitoring and alerting, optimization and scaling, and security and compliance. You will bring a Bachelor's or Master's degree in Computer Science, Engineering, or a related field, strong programming skills, experience with ML frameworks and libraries, proficiency in cloud platforms and containerization technologies, familiarity with CI/CD tools and version control systems, and a solid understanding of DevOps principles and practices. You will also contribute to a customer-focused, driven-to-win organization with leading-edge products, and be part of an inclusive, diverse, multinational company that values culture fit and culture-add. If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with Proofpoint.