Introduce the job. self introduction. Machines learning questions and optimizations questions. Finally, two behavior questions, what difficulties have been met and how is it solved?
Introduce the job. self introduction. Machines learning questions and optimizations questions. Finally, two behavior questions, what difficulties have been met and how is it solved?
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)