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Machine Learning Engineer Interview Experience

March 1, 2024
Negative ExperienceNo Offer

Process

This was a phone screen, consisting of three parts:

  • 20 minutes of values
  • 20 minutes of coding
  • 20 minutes of applied ML

Values

Pretty standard behavioral questions, such as describing a situation.

Coding

Asked a hard LeetCode question about how to get the median of two sorted arrays (LeetCode #4).

Applied ML

Asked to explain an attention layer.

In the end, I feel like even for an MLE role, this was on the advanced side for both DSA and ML theory, which doesn't sound reasonable. On top of this, the interviewer had horrible communication skills and couldn't answer even the most basic questions properly.

Questions

Given two sorted arrays, nums1 and nums2, of size m and n respectively, return the median of the two sorted arrays. The overall run time complexity should be O(log(m+n)).

Explain the attention layer, self-attention, cross-attention, and multi-head attention layer.

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Interview Statistics

The following metrics were computed from 18 interview experiences for the Snap Machine Learning Engineer role in United States.

Success Rate

6%
Pass Rate

Snap's interview process for their Machine Learning Engineer roles in the United States is extremely selective, failing the vast majority of engineers.

Experience Rating

Positive33%
Neutral17%
Negative50%

Candidates reported having negative feelings for Snap's Machine Learning Engineer interview process in United States.

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