CV Compiler is a robot that fixes your resume to make you more competitive

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Machine learning is everywhere now, including recruiting. Take CV Compiler, a new product by Andrew Stetsenko and Alexandra Dosii. This web app uses machine learning to analyze and repair your technical resume, allowing you to shine to recruiters at Google, Yahoo and Facebook.

The founders are marketing and HR experts who have a combined 15 years of experience in making recruiting smarter. Stetsenko founded Relocate.me and GlossaryTech while Dosii worked at a number of marketing firms before settling on CV Compiler.

The app essentially checks your resume and tells you what to fix and where to submit it. It’s been completely bootstrapped thus far and they’re working on new and improved machine learning algorithms while maintaining a library of common CV fixes.

“There are lots of online resume analysis tools, but these services are too generic, meaning they can be used by multiple professionals and the results are poor and very general. After the feedback is received, users are often forced to buy some extra services,” said Stetsenko. “In contrast, the CV Compiler is designed exclusively for tech professionals. The online review technology scans for keywords from the world of programming and how they are used in the resume, relative to the best practices in the industry.”

The product was born out of Stetsenko’s work at GlossaryTech, a Chrome extension that helps users understand tech terms. He used a great deal of natural language processing and keyword taxonomy in that product and, in turn, moved some of that to his CV service.

“We found that many job applications were being rejected without even an interview, because of the resumes. Apparently, 10 seconds is long enough for a recruiter to eliminate many candidates,” he said.

The service is live now and the team expects the corpus of information to grow and improve over time. Until then, why not let a machine learning robot tell you what you’re doing wrong in trying to get a job? That is, before it replaces you completely.

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