Ying currently works in Lyft's streaming platform team, where he investigates large-scale near real-time data ingestion and streaming pubsub infrastructure. Prior to Lyft Inc, he worked at Linkedin where he designed kafka-driven cross data center replication for Espresso -- Linkedin's scalable, time-line consistent source-of-truth NoSQL database.

Kailash has over 5 years of experience building data infrastructure, search infrastructure and computer vision systems. During his time at Lyft, Kailash has worked in teams which manage kafka cluster, build flink jobs to persist data to S3 and manage platform for real-time distribution of messages / events. In his erstwhile life, he worked as an investment banker advising corporates on IPO / M&A strategies.