[Discussion] How much non-ml prepping does a researcher need for amazon applied ml scientist interviews?

I successfully interviewed for an amazon applied ml internship (but did not take the offer). PhD student at top uni.

Interview was a series of:

- Phone interview with senior research scientist -> Explain recent project, discuss my background around their subfield. Heavy focus on Amazon's core values (this is very central to the application process).


- 1st: Whiteboard coding, discussion of my background with research scientists. Explain my CV and current research.

- 2nd: Again research project background discussion, then questioning around Amazon's core values and how I have reflected or internalized each one of them.

- 3rd: Lab director. Higher level discussion, then some pointed questions on statistical learning to probe out my background.

On a technical level, the interviewing was much lighter than at e.g. DeepMind. They _really_ do care about those core values so make sure you have a story for every single one.

/r/MachineLearning Thread