tell me something about you
Machine Learning Engineer Interviews
Machine Learning Engineer Interview Questions
Companies rely on machine learning engineers to help design and improve the systems that allow their software to improve on its own, rather than being specifically programmed. During the interview process, be prepared to be tested heavily on both computer science and data science knowledge with an emphasis on recognizing patterns and trends. A bachelor's degree in computer science or a related field will be required.
Top Machine Learning Engineer Interview Questions & How to Answer
Question 1
Question #1: What are the most important algorithms, programming terms, and theories to understand as a machine learning engineer?
How to answer
How to answer: Be prepared to talk about things like Type I and Type II errors, supervised and unsupervised machine learning, ROC curves, and other key parts of machine learning. Employers want to know you have a strong knowledge of the technical aspects of the job position.
Question 2
Question #2: How would you explain machine learning to someone who doesn't understand it?
How to answer
How to answer: Sometimes machine learning engineers have to work with people who aren't familiar with the technical aspects of the job. Use this interview question as an opportunity to show your strong knowledge of the position and your communication abilities.
Question 3
Question #3: How do you stay up to date with the latest news and trends in machine learning?
How to answer
How to answer: By talking about how you're up to date with the latest news and trends in machine learning, you can show an employer that you're engaged in the industry, a skilled researcher, and self-motivated.
8,202 machine learning engineer interview questions shared by candidates
Describe the algorithm mentioned above
what data type cant be used as key in a dictionary?
They never decided to ask me any question.
What were some of the Deep Learning architectures you have developed and why?
It was a long test with very less time for answering the questions. Answers should be right on top your head. One of the Speed Coding question was to find the minimum amount of power that Gandalf should carry so that when he fights with many minions and reaches the boss, he should at least have power = 1.
take home data science homework is free form, you are given a pipeline with a bunch of classifiers that'll predict whether a user is retained or not based on swiping activity, you're told to add whatever you want to the pipeline to showcase your skills the tools are the traditional sklearn/numpy/matplotlib etc and the algos involved are regression/xbgoost/other voting algos
Had an HR round and then a technical round where we talked about projects and then a case study. The issue is that the case study is a tough problem that they are dealing with; that is, something they have a whole team dedicated to and have been thinking about for months to years. Yet you are supposed to solve it in just a few minutes! So it really is not a fair assessment but that's how all tech interviews are today. One thing was the interviewer kept interrupting and didn't let me finish so I just figured he was trying to drive me toward to a set of exploratory questions on the case study. I did answer every question but got turned down.
discussion of semantic segmentation, describe Mask RCNNs/YOLO algorithms, cross entropy, graph/DFS type problems, design an optimizer for any cost function f
Test technique à faire chez soi
Viewing 951 - 960 interview questions