Domino Data Lab Named a Winner of Built In’s Best Places to Work Award for Second Year in Row

Domino Data Lab, provider of the leading Enterprise MLOps platform trusted by over 20% of the Fortune 100, announced that Built In has selected it for several of its 2022 Best Places to Work Awards. Following the data-backed selection process, Domino has been honored in Built In’s San Francisco lists of Best Places to Work, Best Midsize Companies to Work For, and Best Paying Companies.

Domino continues to earn praise for its employee satisfaction and the quality of its workplace culture and benefits. Headquartered in San Francisco with a global workforce, this is the second consecutive year Domino has been named by Built In as one of the Best Midsize Companies and Best Paying Companies to work for in San Francisco.

“Each member of our team comes from a unique background and has different experiences which help us foster an environment of creativity and problem solving,” said Nick Elprin, CEO and co-founder of Domino Data Lab. “This culture promotes our team’s devotion to customers and helps us deliver results to the most sophisticated companies in the world.”

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Built In determines the winners of Best Places to Work based on an algorithm, using company data about compensation, benefits, and companywide programming. To reflect the benefits candidates are searching for more frequently on Built In, the program also weighs criteria like remote and flexible work opportunities, programs for DEI, and other people-first cultural offerings.

“It is my honor to extend congratulations to the 2022 Best Places to Work winners,” says Sheridan Orr, Chief Marketing Officer, Built In. “This year saw a record number of entrants — and the past two years fundamentally changed what tech professionals want from work. These honorees have risen to the challenge, evolving to deliver employee experiences that provide the meaning and purpose today’s tech professionals seek.”

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Domino Data LabEnterprise MLOpsFortune 100MLOps platformWorkplace culture
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