Cracking A MLE Interview

I have worked as a ML Sourcer for the last 4 years and here are some resources that my candidates have shared with me. I hope its helpful.

First round:?

HackerRank/LeetCode Interview:

Typically, big-tech companies have a 1-hour technical phone screen that comprises 1 LeetCode style question followed by 10 to 15 mins of rapid-fire ML tech questions towards the end.

Book : Algorithm Design Manual: will teach you the math behind all of the data structures and algorithms you can expect to see during an interview. Learn the techniques needed to solve the more difficult programming.

How to use

In order to pass your programming interview you need to go deeper with your understanding.

Other resources:?

Textbook and this Coursera course.?

Onsite Interview:

• Machine learning theory round
• Machine learning system design
• Machine learning coding

Machine learning theory round

This round is quite similar to the above technical assessment round and has 45 min to 1 hour dedicated to it. The objective of this round is more to test your waters and distinguish between an ML modeling engineer and vs. ML Infra engineer.?

YouTube playlist

Machine learning system design

course?

Expect questions like

• Design a feed recommendation system
• Design Youtube(Google)
• Design Google contact ranking(Google)
• Design an item replacement recommendation(Instacart)
• Design an ML System to optimize coupon distribution with a set budget(Netflix).

Helpful resources:?

Resource 1

Resource 2

Behavioral Round

Resource1?

Youtube?

Web

#interviewprep #machinelearning