Explain a machine learning project you’ve worked on. What were the challenges, and how did you address them? How would you approach building a recommendation system for a new product? Discuss the trade-offs between different machine learning algorithms (e.g., decision trees vs. neural networks). How do you handle missing data in your datasets? Explain the concept of regularization and why it’s important.
How does a Transformer work
It wasn’t leetcode style question
Amazon LPs, Machine learning, and Coding
House robber variation from Leetcode
When did you have your mind changed and why?
What motivates you in your career?
2nd onsite interview: Technical/Research questions included: Discussion about employing/improving amazon's image search service (i.e from an instagram fashion post, finding the corresponding product in the amazon catalog) Included potential techniques for large scale image matching, annotation (bboxes, segmentation masks, hierarchical labels etc.), adding new items to the product list, transferring knowledge between similar domains (i.e instagram vs magazine)
What is the interpretation of an ROC area under the curve as an integral?
Few recommendations, - Be ready for typical behavioural questions. Preparation beforehand is a must. - LC easy-medium questions. - Be ready to answer questions related to your past/ongoing projects. Sometimes, the interviewer can go deep into the technical details of the project. - Explore Amazon research beforehand and figure out where your research work fits best and if possible mention this in the interview. - Last but not least, prepare a few questions you would like to ask the interviewer in the end (there will be dedicated time for that) Overall, it's a great experience and you get to learn a lot. Best of luck!
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