Had a couple of interviews. 3 coding rounds, one deep dive into deep learning, and ML design interview. The coding round interview questions were leetcode medium and hard questions. The interviewers were helpful and guided me so I was able to do them within reasonable. Be mindful of edge cases. ML design question is open ended, hard to prepare for. You are asked to design a predictive system and are told to focus on the machine learning side of things. Make sure to gather requirements (scale, scope, metrics to improve) before diving in. Talk about data collection, think what kind of a data a company like Meta collects and how you could label it and use it, what other data sources could you use, how would you go about collecting them and how would you label them. Be prepared to talk in detail about the ML model you think you should be using and defend the choice if needed.
Learning Technology Interview Questions
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Two algorithm online assessment Three panel interviews questions, one brain teaser, one algorithm and one system designed.
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What was the most difficult technical challenge you had to face
Desigining Scalabale Machine Learning based solution for a regualr usecase
the same as on Leetcode
Design ml system for posts comments
How would you prepare for cultural differences when training? How would your past experiences prepare you to train enterprise clients?
leetcode question: finding exit in a maze, finding the largest number in the number stream.
Leetcode tag problems; middle difficulty.
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