Process
Asked an easy and a hard LeetCode question in the phone screen.
It was very difficult to make them bug-free and finish two questions in 40 minutes.
I didn't expect hard questions for an MLE role as well.
Good luck, everyone!
Questions
Calculator question on Leetcode. Difficult to finish within 20 minutes.
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Interview Statistics
The following metrics were computed from 92 interview experiences for the Meta Machine Learning Engineer role in United States.
Success Rate
11%
Pass Rate
Meta's interview process for their Machine Learning Engineer roles in the United States is extremely selective, failing the vast majority of engineers.
Experience Rating
Positive53%
Neutral26%
Negative21%
Candidates reported having very good feelings for Meta's Machine Learning Engineer interview process in United States.
Meta Work Experiences
2.0
High compensation overshadowed by toxic culture and pressure
Machine Learning Engineer • Current Employee
Seattle, WA
May 6, 2026
Pros: High total compensation is the only one.
Cons: Backstabbing.
High pressure.
Fast pace.
Toxic culture.
5.0
Intense Environment, Excellent Company
Machine Learning Engineer • Former Employee
Mountain View, California, United States
March 19, 2021
Pros: Good company, good environment, high pressure.
Cons: High peer pressure, fast work tempo
1.0
Always a looming threat of being kicked out
Machine Learning Engineer • Current Employee
Menlo Park, CA
February 2, 2026
Pros: Good infra; MLEs don't waste time on DevOps.
Cons: There was always a looming threat of being kicked out.
- 2.0High compensation overshadowed by toxic culture and pressureMachine Learning Engineer • Current EmployeeSeattle, WAMay 6, 2026Pros: High total compensation is the only one.Cons: Backstabbing. High pressure. Fast pace. Toxic culture.
- 5.0Intense Environment, Excellent CompanyMachine Learning Engineer • Former EmployeeMountain View, California, United StatesMarch 19, 2021Pros: Good company, good environment, high pressure.Cons: High peer pressure, fast work tempo
- 1.0Always a looming threat of being kicked outMachine Learning Engineer • Current EmployeeMenlo Park, CAFebruary 2, 2026Pros: Good infra; MLEs don't waste time on DevOps.Cons: There was always a looming threat of being kicked out.
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