J'ai postulé via la recommandation d'un employé. J'ai passé un entretien chez Amazon (New York, NY) en févr. 2022
Entretien
Applied through a LinkedIn connection. I refused to interview with them several times, so it took several months. The phone screen was very reasonable. They asked about basic ML stuff and then a simple question on binary trees. Final interview was not that difficult, but I didn't have a lot of experience with deep learning, so I got rejected.
Questions d'entretien [1]
Question 1
Mostly deep learning stuff. One ML design interview. One data structure problem on coder pad. Most of the interviews are focused on their principles.
J'ai postulé via un recruteur. J'ai passé un entretien chez Amazon (Seattle, WA) en juin 2026
Entretien
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
Questions d'entretien [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)
Candidature
J'ai passé un entretien chez Amazon (Santa Monica, CA)
Entretien
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