Design, implement, and maintain robust, containerized, and reproducible pipelines for model training, evaluation, and deployment—across both batch and real-time settings. Build and manage ML services, APIs, and model serving infrastructure using tools like MLflow, Amazon SageMaker, and Feature Store. You will set up and maintain monitoring, observability, and alerting systems to ensure high availability and performance, and continuously evaluate emerging MLOps technologies to improve efficiency, scalability, and reliability.