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I most recently interviewed for ML Engineering roles in October-December 2021. I interviewed for companies ranging from FAANG to consulting groups to startups. This article is a brief overview of the materials I used to study and some of the interview questions I was asked. I wanted to share my resources for studying while they were fresh on my mind. I ended up getting MLE offers at several companies (including Google and the healthcare startup I’m currently at).
Many online resources recommend spending 5–6 months studying for interviews, but I crammed my studying into 2 months. I won’t say it was the most ideal but it definitely is possible if you’d rather just grind for a shorter period of time and get the interview process over with.
Below is my study strategy and approximately how I split up my time:
- General ML (65%)
- Behavioral Interviews (5%)
- Software Engineering (20%)
- Company Specific (10%)
Part 1 — General ML
Concepts
As a bare minimum, I recommend watching Andrew Ng’s Deep Learning Specialization. Many of the concepts may be already familiar to you but it’s nice to brush up on the concepts, even if…