- First round was a ~45-min presentation on a prior project. - One design question with the hiring manager seeing how I would approach the problem they are working on. This was the most technically difficult interview - One leetcode medium question with a software engineer. - Other rounds were a mix of behavioral questions and technical questions about CV/ML. - Each round had multiple behavioral questions (maybe half the time or more). I could tell they wanted me to be specific on my direct involvement and were gauging both how well I handled certain situations and how I could explain my core values. Overall not a very difficult interview, as long as you have solid examples for the behavioral questions/leadership principles. The technical aspect was actually far easier than several other non-FAANG companies I interviewed with.
Applied Scientist Interview Questions
1,182 applied scientist interview questions shared by candidates
Random forest vs decision tree
1) When you receive a critical feedback 2) When you find a significant problem in your team
Some questions that were asked: - Can you perform linear regression when two features are identical? - How would you train a logistic regression model when you have many more 0’s than 1’s in your training set? - What are problems with drop-out regularization and how are they tackled? - Why does L2 regularization work better than L1 regularization? - What are random forests? The interview ended with a programming challenge on a (virtual) whiteboard. It was a hard challenge that I could not solve within the ca. 10 minutes that I was given. Having two people watch what you type of course doesn't help.
Some ml questions, some algorithm questions
Write a SQL query to join two tables.
If I am ok with more than 50% time product level coding
Amazon Leadership principles: Leaders are right, a lot Leaders keep moving forward etc.
gradient descent and learning rate
1. Max Product sub array 2. Boundary Nodes of Binary Tree.
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