AWS Architect

Understanding business requirements and translating them into scalable and efficient machine learning architectures on AWS SageMaker.o Designing end-to-end machine learning pipelines, including data ingestion, processing, model training, deployment, and monitoring.o Selecting appropriate AWS services and features, including SageMaker built-in algorithms, custom models, and other relevant AWS services like S3, EMR, etc.Implementation and Deployment:o Building and deploying machine learning models and infrastructure on AWS SageMaker, including configuring SageMaker instances, endpoints, and pipelines.o Ensuring the scalability, reliability, and security of the machine learning platform.o Implementing best practices for MLOps (Machine Learning Operations) to automate the machine learning lifecycle.Skills and Expertise:

• Deep understanding of AWS SageMaker: Including its features, capabilities, and best practices.
• Strong knowledge of machine learning concepts: Model building, training, evaluation, and deployment.