it was about combining sorted lists
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.
8,195 machine learning engineer interview questions shared by candidates
The first one is related to merge sort, and second one a DP question
Explain LSTMs and why they are used? What are the advantages and disadvantages when you compare other architectures. And some follow up questions about it.
The coding interview was one of the most comfortable I had. It was with a very experienced person who made sure to be kind, understanding and open-minded. The ML interview however was by some rude woman possibly going through a mid life crisis, that she decides to take it out on you. From the start of the interview where she turned up late to putting down the candidate's accomplishments, she made sure to make the candidate uncomfortable. At the end when it was my turn to ask a question and I did, she decided to ask me a question back without answering it. That's how arrogant she was. The surprising part is, they took 2 weeks to find a person to conduct the ML interview, since they didn't have many ML experts inside. And they found an insufferable one.
LeetCode problems I've worked on include 227, 680, 1650, and a question about sampling a city based on its population.
Mention some ML algorithms you have worked with
How do you import a function?
What are the different data structures in Python?
They asked if I was to make a project on document extraction project. This was because i was interviewing for that particular team and project. They also asked an array-related probability-related question. It was like there were random numbers in an array and then each element had some weight associated with it. so i had to output an array calculating the probability based on the weights assigned to each element.
Talk about a project you worked on and how it will relate to the job.
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