Job Description
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.