• Design, train, and deploy a wide range of AI/ML models for mission-critical applications, ensuring they meet performance and scalability requirements. • Implement and manage automated MLOps pipelines for model monitoring, retraining, and lifecycle management to ensure continuous delivery and reliability. • Optimize model performance, scalability, and resource consumption in production cloud and on-premise environments. • Collaborate with data scientists, software engineers, and systems architects to translate model prototypes into hardened, production-grade solutions. • Uphold software engineering best practices, including robust version control, comprehensive testing, and CI/CD processes. • Stay current with industry trends and best practices in MLOps and operational AI to continuously improve the team's capabilities.