none of the questions were technical, the interviewers were just totally disinterested in my profile, all their questions were pointless like they had not bothered to read my CV/resume.
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.
8,212 machine learning engineer interview questions shared by candidates
How would you go about creating a ML pipeline
How do you give and encourage feedback?
Explain self-attention? How is it different from attention? How is used in transformers? Some questions about Inverted dropout. How can one make sure that a certain number of parameters in a Deep Network are trained?
What is Optimisation in Deep Learning
What are the pros and cons of LR, SVM, and random forests? How do you choose them?
Fundamental of ML, algorithm design, and programming questions
Explain how hyper parameter tuning had an impact to the overall algorithm and how it could be further optimized
Why might one use a support verctor-based algorithm instead of deep learning
Talk about your PhD research. Did you use machine learning and, if not, why not?
Viewing 2641 - 2650 interview questions