Process
I applied through an employee referral. The process took two weeks.
- Recruiter call: 30 minutes.
- Phone-screen: Coding, LeetCode medium, 45 minutes.
- Virtual on-site: Two coding rounds (LeetCode medium), two system design rounds, and one behavioral round.
Once I passed all rounds, there was a hiring manager call to learn about the team.
Questions
Coding rounds ask standard LeetCode Medium questions. It helped to study the frequently asked questions. System designs were also pretty straightforward.
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Interview Statistics
The following metrics were computed from 161 interview experiences for the Meta Machine Learning Engineer role.
Success Rate
12%
Pass Rate
Meta's interview process for their Machine Learning Engineer roles is extremely selective, failing the vast majority of engineers.
Experience Rating
Positive57%
Neutral23%
Negative20%
Candidates reported having very good feelings for Meta's Machine Learning Engineer interview process.
Meta Work Experiences
4.0
Great learning experience
Machine Learning Engineer • Former Employee
Menlo Park, California, United States
March 23, 2023
Pros: A fast-growing environment for high performers, with an open and transparent work culture.
Cons: Too fast for medium/low performers.
3.0
Cool, but too unstable
Machine Learning Engineer • Current Employee
London, England, United Kingdom
November 21, 2022
Pros: Great amenities, good work locations, amazing perks.
The development culture is very open and light. There is a focus on producing impact, which is very nice.
Cons: The ad market is very unstable, and things around the metaverse are crude at the moment.
5.0
Hard work while being treated well
Machine Learning Engineer • Current Employee
Seattle, Washington, United States
April 10, 2020
Pros: Fair evaluations, challenging problems, supportive peers and managers.
Cons: The competitive environment pushes some people to work extra hours.
- 4.0Great learning experienceMachine Learning Engineer • Former EmployeeMenlo Park, California, United StatesMarch 23, 2023Pros: A fast-growing environment for high performers, with an open and transparent work culture.Cons: Too fast for medium/low performers.
- 3.0Cool, but too unstableMachine Learning Engineer • Current EmployeeLondon, England, United KingdomNovember 21, 2022Pros: Great amenities, good work locations, amazing perks. The development culture is very open and light. There is a focus on producing impact, which is very nice.Cons: The ad market is very unstable, and things around the metaverse are crude at the moment.
- 5.0Hard work while being treated wellMachine Learning Engineer • Current EmployeeSeattle, Washington, United StatesApril 10, 2020Pros: Fair evaluations, challenging problems, supportive peers and managers.Cons: The competitive environment pushes some people to work extra hours.
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