I have 15 years of industry experience as a software developer most of it building distributed infrastructure to store and search data in realtime.
I lead the core search team at Yelp. During this time I have been instrumental in modernizing Yelp’s search infrastructure and moved it from a custom distributed lucene based ranking application to a generalized ranking application built on top of elasticsearch. I wrote a custom geocoder for Yelp to help mitigate reliance on third party geocoders. This systems now serves majority of the geocoding traffic at Yelp.
Lately I have been working on building a ranking platform at Yelp which enables multiple teams at Yelp to quickly deploy their machine learned models on elasticsearch for customized scoring.
I am an open source contributor for elasticsearch(https://github.com/elastic/elasticsearch/commits?author=umeshdangat) and a collaborator on the learning to rank plugin (https://github.com/o19s/elasticsearch-learning-to-rank/commits?author=umeshdangat) for elasticsearch. I will be speaking at the Haystack search relevance conference (https://haystackconf.com/) in New York, April 2019.