I applied online. The process took 5 weeks. I interviewed at Amazon (Sunnyvale, CA) in Apr 2022
Interview
The first Screening Interview was with a member of the team. It was several technical questions about computer vision and one leetcode medium problem in coderpad that was relevant to CV (think matrix manipulation). I mostly solved it with a few hints. Technical questions were broad and did not get very deep.
The Onsite Interview was five 1-hour rounds.
The offer was very high (30% higher than comparable positions at other companies), but the horror stories of long work weeks and the danger of PIP steered me toward a lower paying role that I think I'd be happier in.
Interview questions [1]
Question 1
- 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.
I applied through a recruiter. I interviewed at Amazon (Seattle, WA) in June 2026
Interview
This interview was for the Applied Scientist Position at Amazon. It was a Science breadth/Depth as well as 1 easy LC problem. After that did a full loop interview. 1 Science ML Breadth, 1 Science Depth, 1 Sys Design (Team-specific), 1 coding round and 1 Bar Raiser
Interview questions [1]
Question 1
Bias-Variance tradeoffs. Bagging Vs boosting. Modeling details in my project. Basic Statistical Questions. DSA: String compression problem.
1 HR round
4 technical interviews (coding+depth+breadth) of Machine Learning.
1 round to go into depth of my own projects.
1 round on general data science questions + system design (model a pipeline end-to-end for translating one set of multimodal objects to another language)
Two easy Leetcode problems, some ML coding problems and a lot of Leadership Principles talk. Overall average experience. A lot of middle managers not much room to innovate or take risks. Like working for the DMV