It’s a problem that recruiters and candidates alike are all too familiar with: poorly written job descriptions that do little to direct the right talent to the right open positions abound. To make it even worse, many resumes are similarly uninformative, making it equally challenging for employers to find the right candidates through simple keyword searches. Google has stepped in to do something about this bidirectional mess.
In a blog post on November 15, 2016, Google announced it’s now job-match API, Cloud Jobs. “Hiring is one of the hardest things organizations do” says the post. “Part of the difficulty comes from a lack of industry standards to define and describe occupations and how they align to specific skills.” Google’s Cloud Jobs aims to change that.
A part of Google Cloud Machine Learning group, Cloud Jobs is currently in the alpha testing phase and available only to a limited number of companies. In its complete form, Cloud Jobs will be a big, free to use API that boasts a really smart, intuitive job match algorithm to pair job seekers with relevant positions. Anyone will be able to use it and, when used in combination with applicant tracking systems (ATSs), will allow companies to better leverage contacts from previous applications to fill new job openings.
When candidates search for keywords, Cloud Jobs also searches for industry- and company-specific jargon that refers to the same positions. This is incredibly helpful for matching job seekers searching in plain English to position descriptions written in jargon.
Job descriptions are all too often incomplete. Cloud Jobs fills in missing information, like company street addresses, employment type, and benefits, where appropriate.
Some job seekers prioritize short commute times, or simply aren’t willing to have commutes that take longer than a certain amount of time. Cloud Jobs can translate street addresses and colloquial regions like ‘Bay Area’ or ‘Research Triangle’ to precise geo-coordinates. This allows job seekers to filter based on distance and commute times.
It’s incredibly frustrating, for example, for a mid-level job seeker to search for a specific job opening and receive dozens of listings that are entry- or senior-level. Cloud Jobs understands seniority so that it only presents relevant results to job seekers.
Job seekers can mark the jobs that they like and the jobs that they don’t. Cloud Jobs then uses that information to tailor the results it presents. The more that a job seeker uses Cloud Jobs, the more specific the results become.