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 Jun 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.
I applied through a recruiter. I interviewed at Amazon (Seattle, WA) in May 2026
Interview
The process started with a technical phone screen, followed by four back-to-back rounds. The first two technical rounds focused on ML breadth and ML depth respectively, while the later rounds focused more on system design, agentic product thinking, and behavioral examples.
Interview questions [1]
Question 1
Design an agentic recommendation system. How would you structure the system, what models or components would you use, and how would you evaluate its quality and safety?
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)