Meta

Machine Learning Engineer Interview Experience

November 1, 2019

Positive ExperienceGot Offer

Process

The process begins with two rounds of coding interviews, each lasting 45 minutes.

After successfully passing the technical interviews, candidates proceed to three rounds of team matching.

Teams are selected based on a survey that candidates previously filled out.

Questions

In the first round, there was one hard question from LeetCode.

In the second round, there were one easy and one medium question.

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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

Meta Machine Learning Role Interview Experience

Machine Learning Engineer • Current Employee

Seattle, Washington, United States

Pros: Recruiter was super friendly and helpful throughout. Easy to reschedule interviews as needed. Behavioral round felt conversational, not forced. You get a chance to ask meaningful questions.

Cons: 45 minutes per round felt tight, especially for coding. The process almost took 3 months. I think Meta is not hiring STEM OPT candidates; not sure though.

Meta Machine Learning Role Interview Experience

Machine Learning Engineer • Current Employee

Seattle, Washington, United States

Pros: Recruiter was super friendly and helpful throughout. Easy to reschedule interviews as needed. Behavioral round felt conversational, not forced. You get a chance to ask meaningful questions.

Cons: 45 minutes per round felt tight, especially for coding. The process almost took 3 months. I think Meta is not hiring STEM OPT candidates; not sure though.

Good place to work, chaotic

Machine Learning Engineer • Current Employee

Menlo Park, California, United States

Pros: Surrounded by the best engineers, there's a lot to learn.

Cons: It's been very chaotic since the layoffs.

Good place to work, chaotic

Machine Learning Engineer • Current Employee

Menlo Park, California, United States

Pros: Surrounded by the best engineers, there's a lot to learn.

Cons: It's been very chaotic since the layoffs.

Remote Work, Mixed Feelings

Machine Learning Engineer • Former Employee

San Francisco, California, United States

Pros: Nice people to work with. Position 100% remote.

Cons: Didn’t get a great feel for the company. Was part of a mass layoff after less than a year of employment. I left a very good job for them, which was so disappointing. But I did receive a good exit package.

Remote Work, Mixed Feelings

Machine Learning Engineer • Former Employee

San Francisco, California, United States

Pros: Nice people to work with. Position 100% remote.

Cons: Didn’t get a great feel for the company. Was part of a mass layoff after less than a year of employment. I left a very good job for them, which was so disappointing. But I did receive a good exit package.

Meta Machine Learning Role Interview Experience

Machine Learning Engineer • Current Employee

Seattle, Washington, United States

Pros: Recruiter was super friendly and helpful throughout. Easy to reschedule interviews as needed. Behavioral round felt conversational, not forced. You get a chance to ask meaningful questions.

Cons: 45 minutes per round felt tight, especially for coding. The process almost took 3 months. I think Meta is not hiring STEM OPT candidates; not sure though.

4.0
Meta Machine Learning Role Interview Experience
Machine Learning Engineer • Current Employee
Seattle, Washington, United States
July 7, 2025
Pros: Recruiter was super friendly and helpful throughout. Easy to reschedule interviews as needed. Behavioral round felt conversational, not forced. You get a chance to ask meaningful questions.
Cons: 45 minutes per round felt tight, especially for coding. The process almost took 3 months. I think Meta is not hiring STEM OPT candidates; not sure though.

Good place to work, chaotic

Machine Learning Engineer • Current Employee

Menlo Park, California, United States

Pros: Surrounded by the best engineers, there's a lot to learn.

Cons: It's been very chaotic since the layoffs.

4.0
Good place to work, chaotic
Machine Learning Engineer • Current Employee
Menlo Park, California, United States
June 16, 2023
Pros: Surrounded by the best engineers, there's a lot to learn.
Cons: It's been very chaotic since the layoffs.

Remote Work, Mixed Feelings

Machine Learning Engineer • Former Employee

San Francisco, California, United States

Pros: Nice people to work with. Position 100% remote.

Cons: Didn’t get a great feel for the company. Was part of a mass layoff after less than a year of employment. I left a very good job for them, which was so disappointing. But I did receive a good exit package.

3.0
Remote Work, Mixed Feelings
Machine Learning Engineer • Former Employee
San Francisco, California, United States
June 2, 2023
Pros: Nice people to work with. Position 100% remote.
Cons: Didn’t get a great feel for the company. Was part of a mass layoff after less than a year of employment. I left a very good job for them, which was so disappointing. But I did receive a good exit package.

Meta Interview Questions

Minimum Remove to Make Valid Parentheses

Given a string with parentheses, determine the minimum number of parentheses you must remove to make the string valid. A valid string has balanced and properly nested parentheses.

StringsStacksTwo Pointers

Valid Word Abbreviation

Determine if a given abbreviation is valid for a given word. An abbreviation can contain digits representing the number of skipped characters.

StringsTwo Pointers

Binary Tree Vertical Order Traversal

Traverse a binary tree and return a list of node values for each vertical line, ordered from left to right. Nodes on the same vertical line should be ordered from top to bottom.

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