As a candidate, I’ve been interviewed at a dozen big companies and startups. I’ve got offers for machine learning roles at companies including Google, NVIDIA, Snap, Netflix, Primer AI, and Snorkel AI. I’ve also been rejected at many other companies. Valerii: Yeah, everybody – from a software engineer to a machine learning engineer. All these people go through system design. So that's why the audience, by definition, is larger. ( 34:56)

Alexey: [laughs] Okay, I think that's all we have time for. So maybe last one – How can people find you? ( 1:00:03)Alexey: [laughs] That’s cool. The question is about the book you mentioned – the book was Machine Learning Design Patterns, right? ( 52:56) Valerii: Well, you can find me on LinkedIn. Just type in my name, you use a y instead of ii. With the new rules, it should be ii at the end. ( 1:00:12) This book is not a replacement to machine learning textbooks nor a shortcut to game the interviews. It’s a tool to consolidate your existing theoretical and practical knowledge in machine learning. The questions in this book can also help identify your blind/weak spots. Each topic is accompanied by resources that should help you strengthen your understanding of that topic.

You’ll be expected to set up a system effectively in an ML interview. Let’s discuss the thought process required to answer an interviewer’s questions. NOTE: there are a lot of companies that do NOT ask leetcode questions. There are many paths to become an MLE, you can create your own path if you feel like leetcoding is a waste of time. Modelling is one of the key skills for any ML practitioner, and you want to show your depth in this area. There’s so many techniques for modelling, it’s good to cover some breadth instead of naming one solution. Model Types Alexey: Then at what level would they ask this – I think you were saying level four, which is the Middle Level and level five, which is a Senior. ( 55:07)Alexey: Perhaps if you cover all these parts during your system design interview, you're already in quite a good position. Right? ( 46:02) Text: There’s a lot of valuable data in text. It’s good to have some basic understanding of NLP concepts so you can discuss how to present text to a model. It’s become common place to use embeddings for this, so understand how systems like BERT and Word2Vec can be used. You don’t need to be an expert, but a bit of knowledge of common techniques will make this so much smoother. Machine Learning System design is now available, you can get the course on educative.io here and interviewquery.com Section