Machine Learning Engineer Interview Experience - Canada
October 24, 2023
Positive ExperienceGot Offer
Process
Phone Screening.
Two coding challenges, each lasting 45 minutes.
Candidates need to understand the given scenario, interpret the question, and then choose the appropriate algorithm and data structure to solve it.
After coding, candidates must provide the time and space complexity of their algorithm.
Questions
What is the minimum number of parentheses to add to make a string balanced?
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Interview Statistics
The following metrics were computed from 14 interview experiences for the Meta Machine Learning Engineer role in Canada.
Success Rate
7%
Pass Rate
Meta's interview process for their Machine Learning Engineer roles in Canada is extremely selective, failing the vast majority of engineers.
Experience Rating
Positive64%
Neutral14%
Negative21%
Candidates reported having very good feelings for Meta's Machine Learning Engineer interview process in Canada.
Meta Work Experiences
5.0
Challenging Projects, High Pressure
Machine Learning Engineer • Current Employee
Menlo Park, California, United States
July 23, 2024
Pros: Interesting projects to work on
Cons: Pressure to perform all the time.
4.0
All right, place to work
Machine Learning Engineer • Current Employee
Bellevue, Washington, United States
March 8, 2025
Pros: 1. Work is pretty interesting and enjoyable.
2. Compensation is not bad.
Cons: 1. Tons of politics and scope stealing, which makes the enjoyable work feel much less rewarding.
2. Diversity issues: I was the only person on a team of 10 who couldn't speak a certain language and was frequently left out of discussions.
4.0
Facebook Job Review
Machine Learning Engineer • Former Employee
New York, New York, United States
April 19, 2021
Pros: Coworkers are friendly, self-driven, curious, and talented.
Cons: The environment is very fast-paced and there's poor documentation.
- 5.0Challenging Projects, High PressureMachine Learning Engineer • Current EmployeeMenlo Park, California, United StatesJuly 23, 2024Pros: Interesting projects to work onCons: Pressure to perform all the time.
- 4.0All right, place to workMachine Learning Engineer • Current EmployeeBellevue, Washington, United StatesMarch 8, 2025Pros: 1. Work is pretty interesting and enjoyable. 2. Compensation is not bad.Cons: 1. Tons of politics and scope stealing, which makes the enjoyable work feel much less rewarding. 2. Diversity issues: I was the only person on a team of 10 who couldn't speak a certain language and was frequently left out of discussions.
- 4.0Facebook Job ReviewMachine Learning Engineer • Former EmployeeNew York, New York, United StatesApril 19, 2021Pros: Coworkers are friendly, self-driven, curious, and talented.Cons: The environment is very fast-paced and there's poor documentation.
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