How To Successfully Land A Machine Learning Engineering Interview

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5 Steps to ACE Machine Learning Engineer Interview:
0:00 Introduction
As machine learning engineering roles are highly in demand, interviewing for these positions can be quite tricky. It is definitely different when compared to interviewing for software engineering roles, so in this video I will break down the 5 steps you need to take in order to successfully land the ML engineering interview.
0:42 Step 1 - Self Assessment
In step 1 It's important that you carry out a self assessment of your ML knowledge. If you want to learn machine learning, you can follow my roadmap to learn machine learning and that can be extremely useful.
1:52 Step 2 - Theoretical Test
In step 2, practice some theoretical questions, this makes up about 10% of the interview questions you will get. There are many resources online for these types of questions.
3:02 Step 3 - Practical Assessment
In step 3, look at your practical experience and do a practical assessment. What type of projects have you worked on? What kinds of frameworks/tools are you familiar with?
3:57 Step 4 - Practical Test
In step 4, prepare for practical questions, these will make up 90% of the interview. Be well prepared to answer questions on your projects and machine learning pipeline.
6:18 Step 5 - Company Specific Test
In step 5, you need to do good research on the company. Get a basic idea of what they are working with and how do they use Machine Learning. Try to see if you have some existing knowledge with the technologies they are using and be prepared to answer specific questions.
Hope this guide is super helpful, please share this video with others! Happy Learning!
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