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💥 What’s New in AI: The ML Powering LinkedIn’s Recruiting Recommendation System  

It’s not a secret that LinkedIn has been one of the software giants that has been pushing the boundaries of ML research and development. In addition to nurturing one of the richest datasets in the world, LinkedIn has been constantly experimenting with cutting-edge ML techniques to make AI a first-class citizen of the LinkedIn experience. The recommendation experience in their Recruiter product required all of LinkedIn’s ML expertise as it turned out to be a unique challenge. In addition to dealing with a huge and constantly growing dataset, LinkedIn Recruiter needs to handle arbitrarily complex queries and filters and deliver results that are relevant to specific criteria. Search environments are so dynamic that it’s really hard to model them as ML problems. In the case of Recruiter, LinkedIn used a three-factor criterial to frame the objectives of the search and recommendation model →find more about an incredibly sophisticated series of search and recommendation algorithms that leverage state-of-the-art ML architectures with the pragmatism of real-world systems (subscription is needed but it’s only $20/YEAR).