Meta to Lay Off 5% of Workforce to Improve Performance

In today’s world, layoffs have become commonplace due to constant restructures and downsizing in companies. In a notable move, Mark Zuckerberg’s company Meta Platforms, previously known as Facebook, has stated that it intends to continue with its firings next week while still accelerating the hiring of machine learning engineers. Employees were notified through internal memos that were leaked to Reuters on Friday.

As reported by Reuters, a notification for layoffs will be sent to affected employees at 5 am local time from most parts of the world, including the US, on Monday, as indicated in posts from Meta’s Head of People Janelle Gale.

In addition, the report says that employees based in Germany, France, Italy, and the Netherlands “because of local regulations” will not qualify for the layoffs. However, employees from more than a dozen countries across Europe, Asia and Africa will be receiving their alerts between February 11 and 18.

A Meta spokesperson declined to discuss the posts, as reported by Reuters. The coverage added that the company has already confirmed last month that it plans to cut 5% of its ‘lowest performers’ and try to backfill at least some of those roles. That memo, in which Gale described the firings as '?performance terminations?', was originally shared by The Information. Unlike prior company broad layoffs, Gale explained in her post that Meta has also decided to not close its offices on Monday and will not provide further communication on these changes.

Earlier on Friday, a different note from Peng Fan, Vice President of Engineering for Monetization, encouraged employees to support the much anticipated cabin fever hiring for additional machine learning engineers and other critical business ‘white elephant’ engineering positions. This is in line with Meta’s strategy of developing and deploying a future looking workforce.

In an earlier note, despite Friday, VP Engineering Monetization Peng Fan also requested other staff members assist with an accelerated search and recruitment of machine learning engineers and other white box fundamental engineering positions.