Applied Scientist applicants have rated the interview process at Amazon with 3.1 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 44% positive. To compare, the company-average is 57.5% positive. This is according to Glassdoor user ratings.
Candidates applying for Applied Scientist roles take an average of 25 days to get hired, when considering 210 user submitted interviews for this role. To compare, the hiring process at Amazon overall takes an average of 28 days.
Common stages of the interview process at Amazon as a Applied Scientist according to 210 Glassdoor interviews include:
Phone interview: 32%
One on one interview: 19%
Presentation: 14%
Skills test: 13%
Group panel interview: 6%
Background check: 5%
IQ intelligence test: 4%
Personality test: 3%
Drug test: 2%
Other: 1%
Here are the most commonly searched roles for interview reports -
I applied online. The process took 1 week. I interviewed at Amazon
Interview
Overall easy interview. Not sure what went wrong.
The interview started with Resume/project discussion. Then I was asked a few ML questions on overfitting and underfitting. Later, discussed a use case and design of image matching algorithm. Finally, reverse LinkedList coding question.
Answered all the questions, for coding took O(n) space for the first solution and later verbally explained O(1) improvement.
Not even a courtesy of leaving feedback. Gah!
Phone screen interview
Then onsite interviews: 5 interviews two on coding and three on science and a tech talk
You choose a topic for the presentation
The science interviews are: one on science depth, one on science breath and one on science applications
Interview questions [1]
Question 1
Question on optimizers; comparing gradient decent, adam optimizer etc
Applied for Amazon AGI. After first round, it will go into full round of multiple interviews. Lots of modern LLM training technic questions. There are still some behavioral questions, but less than general Amazon roles.
Interviewed with 1 phone screen, 1 coding, 2 ml design and 2 lp rounds. Most questions were non-leetcode questions more related to day to day ml implementations. The questions were very practical.