Start United States USA — software How We Used ML While Building (Yet Another) Remote Job Board

How We Used ML While Building (Yet Another) Remote Job Board

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Remote tech jobs aggregators are not perfect. How we improve the job search engine and made job search easier.
Join the DZone community and get the full member experience. It was a nice day at the end of 2020 when we suddenly decided to create another aggregator for remote vacancies, exclusively for IT positions. It would be logical to ask why to make another one when there are already enough of them on the market. The answer is straightforward — we understood how to improve current solutions in at least five parameters: As a matter of fact, it is about the last parameter that I want to tell you today. For anyone who has ever searched for a remote job, it is obvious that often companies offer remote work, but only for citizens of certain countries. There is no separate field on the pages with job descriptions where such restrictions can be displayed most of the time. And there is no search/filter. Therefore, the applicant has to carefully read the text of each vacancy to understand whether it makes sense to respond to it or he/she will definitely not pass based on citizenship. We decided to solve this problem, basically, to show the user only those vacancies for which he/she can really apply, given their citizenship. At first, we thought to solve this problem with simple algorithmic methods. The basic idea was: We are looking for certain keywords in the text, for example: „only“, „remote in“, „authorized to work in“, and so on. We are looking for a „location“ next to the keywords, which, as a rule, was a word with a capital letter. If such a location is found, then it is a restriction. In general, if the vacancy says „USA only“, then this logic works perfectly.

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