Machine Learning Engineer Interview Experience - Menlo Park, California
May 1, 2018
Positive ExperienceNo Offer
Process
HR contacted me and set up a technical screen onsite (since I am in the location).
Had I passed, there would be a day full of onsite interviews (5-6) that involve:
- 2 algo/ds
- 1 sys design
- 1 ML sys design
- 1 manager round.
Questions
Given an infinite chessboard, find the shortest distance for a knight to move from position A to position B.
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Interview Statistics
The following metrics were computed from 11 interview experiences for the Meta Machine Learning Engineer role in Menlo Park, California.
Success Rate
27%
Pass Rate
Meta's interview process for their Machine Learning Engineer roles in Menlo Park, California is very selective, failing most engineers who go through it.
Experience Rating
Positive73%
Neutral18%
Negative9%
Candidates reported having very good feelings for Meta's Machine Learning Engineer interview process in Menlo Park, California.
Meta Work Experiences
5.0
Brilliant Team, Frequent Reorgs
Machine Learning Engineer • Current Employee
Menlo Park, California, United States
March 15, 2024
Pros: Really brilliant coworkers doing amazing things. Some managers really know their tech, so it's very easy to get guidance.
Cons: Too much reorg. People are still on the previous project and get reorged into other teams.
3.0
Great pay, too much pressure
Machine Learning Engineer • Current Employee
Menlo Park, California, United States
May 12, 2025
Pros: Pay is competitive. Work on state-of-the-art AI.
Cons: No work-life balance; everyone cares about short-term goals only.
4.0
Good Pay, Varied Work
Machine Learning Engineer • Current Employee
Menlo Park, California, United States
October 20, 2024
Pros: Good pay, can work on a variety of things.
Cons: The scope is small as there are too many people.
- 5.0Brilliant Team, Frequent ReorgsMachine Learning Engineer • Current EmployeeMenlo Park, California, United StatesMarch 15, 2024Pros: Really brilliant coworkers doing amazing things. Some managers really know their tech, so it's very easy to get guidance.Cons: Too much reorg. People are still on the previous project and get reorged into other teams.
- 3.0Great pay, too much pressureMachine Learning Engineer • Current EmployeeMenlo Park, California, United StatesMay 12, 2025Pros: Pay is competitive. Work on state-of-the-art AI.Cons: No work-life balance; everyone cares about short-term goals only.
- 4.0Good Pay, Varied WorkMachine Learning Engineer • Current EmployeeMenlo Park, California, United StatesOctober 20, 2024Pros: Good pay, can work on a variety of things.Cons: The scope is small as there are too many people.
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