Pros and cons of different approaches to solving a LC problem. ML theory breadth - describe a bunch of techniques.
Machine Learning Consultant Interview Questions
8,188 machine learning consultant interview questions shared by candidates
I was grilled on very nitty-gritty details in DS and ML, starting right from PCA to minute aspects of ML algorithms and it's peripherals in 1st round. In 2nd round no technical questions asked, except the manager said they want someone with 3 - 5 yrs of exp in ML/AI. Total waste of time! -_-
For the programming challenge, I was asked to train an NLP model to predict the product in a customer complaint. The submission was expected to be production-level code (as much as one can do within one week).
describe in detail an ML algorithm of your choice
k-means vs knn, naive bayes, GANs, basics about NLP, ...
I was asked to discuss some LLM projects I had worked on, exploring the technical aspects and including one or two theoretical questions.
How would I approach one case
A large part of the interview focused on my PhD thesis. After I explained my research at the beginning, the interviewers asked in-depth questions to assess how well I understood my own work. Later, they asked machine-learning–related questions relevant to the role, including hypothetical scenarios about how I would approach and analyze a given type of data etc.
Some fundamental machine learning questions and then a deep dive into RAG system components.
Tell us about yourself and your experience?
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