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LinkedIn is one of the favorite recruiting platforms in the market. Everyday, recruiters from all over the world rely on LinkedIn to source and filter candidates for specific career opportunities. Specifically, LinkedIn Recruiter is the product that helps recruiters build and manage a talent pool that optimizes the chances of a successful hire. The effectiveness of LinkedIn Recruiter is powered by an incredibly sophisticated series of search and recommendation algorithms that leverage state of the art machine learning architectures with the pragmatism of real world systems.

It’s not a secret that LinkedIn has been one of the software giants that has been pushing the boundaries of machine learning research and development. In addition to nurturing one of the richest datasets in the world, LinkedIn has been constantly experimenting with cutting edge machine learning techniques in order to make artificial intelligence(AI) a first class citizen of the LinkedIn experience. The recommendation experience in their Recruiter product required all LinkedIn’s machine learning expertise as it turned out to be a very unique challenge. In addition to dealing with an incredibly large and constantly growing dataset, LinkedIn Recruiter needs to handle arbitrarily complex queries and filters and deliver results that are relevant to a specific criteria. Search environments are so dynamic that result really hard to model as machine learning problems. In the case of Recruiter, LinkedIn used a three-factor criterial to frame the objectives of the search and recommendation model.

1) Relevance: The search results need to not only return relevant candidates but to surface candidates that could be interested on the target position.

2) Query Intelligence: Search results should not only return candidates that match a specific criteria but also similar criteria’s. For instance a search for machine learning should return candidates that list data science in their skillsets.

3) Personalization: Very often, finding the ideal candidates for a company is based on matching attributes that fall outside the search criteria. Other times, recruiters are not certain of what criteria to use. Personalizing search results is a key element of any successful search and recommendation experience.

#overviews #linkedin #machine learning #recruitment