Q: You are the ML Engineer who developed a recommendation system model. The model goes into production and behaves not normally, like discrimination or other things. What are you going to do?
Machine Learning Scientist Interview Questions
510 machine learning scientist interview questions shared by candidates
What is your interest region?
Perform exploratory data analysis on given data set, identify by outliers, handle outliers and plot them
Writing loops in Python or other languages
You will be asked a wide range of ML-related questions (ML theory, PyTorch, CNNs, etc.). You will also be asked to code towards the end of the 1 hour session (Leetcode medium). Most of these questions have well-defined answers (e.g., how do you disable gradient computation in PyTorch) while others are more open-ended (e.g., how would you use unlabeled data to boost the performance of your supervised tasks). My major complaints are with these open-ended questions. The interviewer had specific answers in mind and would not understand/accept alternative approaches. The depth of the interviewer's ML knowledge is also questionable as the interviewer did not understand how pretrained networks can be used as feature extractors. The interviewer also asked about variational auto-encoder without knowing the underlying probabilistic formulation. Overall, a negative experience.
Describe your past ML experience
Desired salary range, notice period.
They asked me to describe my project as if I were talking with someone with no background on ML
Algo questions in the online test. Behavioral questions in the phone interview
Asked about relevant experience
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