Google released a new Cloud Jobs API as part of its suit of machine-learning services in the cloud. At least three recruitment websites — CareerBuilder, Dice and Jibe — have signed on so far to use the service, which Google described as “a limited alpha.”
CareerBuilder said in a news release it is currently “running experiments … to power searches on CareerBuilder’s U.S. job site,” and that the trial is “taking place in a test environment with the intention of taking it into production in future.” The aim is to “leverage the scale of Google’s expertise in machine-learning to provide swifter, more relevant results.”
DHI Group, which operates the Dice jobs site, said in its news release it hopes the Cloud Jobs API will allow it “to respond to queries in common language and quickly provide the most relevant job search results.”
In its announcement, Google said the new service “anticipates what job seekers are looking for, and surfaces targeted recommendations,” using machine-learning that “understand[s] how job titles and skills relate to one another, and what job content, location and seniority are the closest match for a job seeker’s preferences.”
We reported in July (in CIR 17.13) that Google was rumored to be working on a job site. If this API is, in fact, what those rumors in the job-board community were referring to, then it’s less a finished product and more of a back-end that could play nicely with existing recruitment advertising sites. That would position Google as a valued supplier and technology provider, rather than a disruptive spoiler to the classified party.
Machine-learning and artificial intelligence in recruitment advertising are fast becoming the hot topic of discussion. Alexander Chukovski of Experteer presented a detailed review of Experteer’s listings capture improvements through the use of machine-learning at last week’s Job Board Summit sponsored by JobG8 in London.
The Cloud Jobs API includes:
- Automatic synonym and acronym expansion — search for a DevOps engineer and you’ll also see jobs for site reliability engineers, for example.
- “Job enrichment” functionality that automatically adds relevant information, such as street address, employment type and benefits.
- Location mapping with precise geo-coordinates.
- Seniority alignment, so that only relevant positions are returned.
- Real-time query broadening to widen a job search’s location, seniority and available positions if there aren’t enough jobs available for the specific search done.
- A “dynamic recommendation engine”, where users can mark which jobs they like and don’t, affecting what positions will be recommended in the future.
“Collaborating with Google is part of our innovation strategy,” CareerBuilder CEO Matt Ferguson said in the statement. “We are a big believer in having an open ecosystem, and we … are confident that utilizing Google’s API will enable us to … dive deeper into solving tougher problems for employers and achieve faster global development down the line.”
The overall Cloud Machine-learning Group will be headed up by Fei-Fei Li, who was director of AI at Stanford, and Jia Li, previously Snap’s head of research. Additional components include translation and natural language APIs, with both free and paid premium versions.
We’ll take a more in-depth look at Google’s Cloud Jobs API in an upcoming issue of Classified Intelligence Report.