Developed an end-to-end ML platform to streamline the training, evaluation, and deployment of machine learning model

Made significant contributions to the design of the low-level diagram, ensuring seamless integration of various components in the platform architecture

Utilized Elasticsearch for project creation and storage, MongoDB for experiment tracking, Kafka as a message broker, Airflow for workflow orchestration, and S3 for secure model storage.

Successfully deployed 5 approved models to production, enhancing efficiency and accuracy in real-world applications