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?
Research Scientist Machine Learning Interview Questions
113 research scientist machine learning interview questions shared by candidates
What is your interest region?
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.
Writing loops in Python or other languages
Describe your past ML experience
They asked me to describe my project as if I were talking with someone with no background on ML
Desired salary range, notice period.
Algo questions in the online test. Behavioral questions in the phone interview
Was asked to discuss a machine learning case study
Asked about relevant experience
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