•Worked on the YouTube team that classifies abusive content using Deep Learning
•Designed and implemented a data pipeline to achieve a 4x performance improvement for reading features required for classification
•Improved the appeal process of an abusive website by providing different versions of features
•Enabled parallel loading of features by moving to new backend system
•Testing the system extensively using unit tests and integration tests
•Technologies Used: C++, Python, Piper, Blaze, Google Cloud Platform, Protobuffers