Techstars grad Adaptilab raises $1.8M to help companies hire machine learning talent

Adaptilab co-founders James Wu (left) and Allen Lu. (Adaptilab Photo)

Machine learning engineers are in high demand. There was a 344 percent jump in number of ML-related job postings from 2015 to 2018, according to Indeed, with an average base salary of $146,085. The machine learning market, meanwhile, is expected to reach $8.8 billion globally by 2022.

Seattle startup Adaptilab is riding these trends with its technical screening platform that helps companies interview potential new hires. Just one year after launching, the Techstars Seattle graduate already has companies such as Experian and Zillow using its technology. And now the company has some cash to fuel its growth.

Adaptilab just raised a $1.8 million seed round led by Bellevue, Wash.-based venture capital firm Trilogy Equity Partners. Other backers include angel investors Kirby Winfield, Bharat Shyam, Ken Glass, Sarah Imbach, and others.

The startup aims to reduce the amount of time and money hiring managers spend interviewing candidates for machine learning roles. Its automated software ranks applicants based on their abilities and provides technical report cards.

(Adaptilab Photo)

Finding machine learning talent is much more difficult than standard engineering hiring, said James Wu, CEO and co-founder of Adaptilab.

“Our initial product is a fully automated technical screening tool that sits at the top of hiring manager’s interviewing funnels,” Wu said. “We can automatically grade candidates’ submitted code to determine how skilled they are at each core competency of machine learning: data preprocessing, data analysis/visualization, feature engineering, model development, model inference, and general programming ability.”

The plan is to start with technical screening and “expand up the vertical to help companies eventually also source, place, and train machine learning engineers,” said Wu, a Duke graduate who co-founded Adaptilab with Allen Lu, who graduated from Carnegie Mellon last year.

AdaptiLab is similar to fellow Seattle startup Karat, which also conducts technical interviews, though AdaptiLab is focused on one specific type of role with machine learning jobs.

Other Seattle-area startups aiming to help companies do a better job of finding employees amid a heated battle for tech talent include SeekOut, Textio, and Fizbuz.

Adaptilab employs three people and plans to grow headcount to 10 within the next year. The company had one of the top pitches at Techstars Seattle Demo Day in May.

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