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At Rivian, over 150,000 vehicles stream 5,500+ signals every five seconds to power push notifications, AI use cases, and analytics in real time. In this talk, we’ll share our evolution from Kinesis, Parquet, and Redshift to a modern streaming stack built on Apache Flink and Apache Kafka. We’ll also cover Event Watch, our spec-driven no-code notification and inference system, and how we operate and optimize it at scale.
I am Staff software engineer at Rivian VW group, I have been a founding engineer at Rivian from October 2021 and we have built the entire realtime stream processing stack here. I am passionate about Realtime stream processing using Apache Flink, Kafka, Schema registry, Druid, Pinot, web application development using Spring-Boot MVC micro services framework, React and Javascript. Prior to Rivian, I was at Yahoo in feed Personalization team where I worked on streaming data for feature engineering and worked closely with data scientists to serve relevant content to users across Yahoo homepage, Yahoo finance etc.
At Stony Brook, Data Science, AI, Operating Systems, Database systems have been my favorite subjects to study. I am passionate about Systems, Networking, Machine Learning. I like to describe myself as a problem solver and I am never shy of adapting to a new technology, tool or language to solve a given problem.
Guruguha is a Staff Software Engineer at Rivian Volkswagen Group Technologies, where he leads multiple real-time data initiatives, mainly on event-driven platforms that cut across different domains. Some of the aspects include real-time event detection platform for telemetry data, near real-time ML inference platform for pre-trained ML models on vehicle telemetry.
