Some machine learning questions (not resume related, more from basic concepts like parameter settings, what should you do if you see XXX happened) and one data structure problem to achieve some functions
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.
8,221 machine learning engineer interview questions shared by candidates
Implement bagging with the given functions
Implement K-means from scratch, Basic ML questions etc
What's the difference between ROC and AUC?
What is regularization? Why is it important? How would you explain logistic regression to someone who didn't know it? What is the difference between optimizers like Adam and SGD with momentum.
1st round: past experience, ML fundamental questions, overfitting, how to address training loss oscillate, how to check data drifting, etc 4 round of Virtual onsite: - 2 codings rounds, one question for each coding round, array, and recursive problem. not in leetcode - 2 ML design: recommendation system and how to design and generate pin embeddings
Implement Decision tree; Implement gradient descent;
Machine learning interview is about designing a system for a specific task.
WORST EXPERIENCE EVER .. ..
What is ReLU activation and Sigmoid activation?
Viewing 4961 - 4970 interview questions