I applied online. The process took 3 months. I interviewed at Amazon (Ámsterdam) in Nov 2024
Interview
The application process consists of a technical screening round, followed by an onsite round if you pass. The onsite round includes six stages: one tech talk and five technical interviews, including ML depth, ML breadth, ML application, and two coding interviews.
While each interview is manageable on its own and there is a wealth of online resources available for preparation, the overall process can feel overwhelming due to its intensity and scope. I also found certain aspects of the procedure to be challenging:
- Frequent changes to information: There were instances where details about the process or expectations were updated unexpectedly, making preparation more difficult.
- Timing issues: Some interviews started later than scheduled, and many extended beyond their planned durations, which disrupted the overall schedule.
- Irrelevant questions: A few interview questions seemed unrelated to the role, making it unclear how they aligned with the position’s requirements.
One key note for potential candidates: Amazon places a significant emphasis on behavioral questions, which can constitute up to 50% of the interview process. It's essential to be well-prepared for these as they are a critical part of the evaluation.
Interview questions [1]
Question 1
The technical questions covered a broad range of foundational topics, including statistics and probability theory, optimization, deep learning, reinforcement learning, causal inference, and generative AI. The most challenging (and quite unexpected) questions for me included those on the Hoeffding inequality and second-order optimizers.
I applied through other source. The process took 3 weeks. I interviewed at Amazon (Seattle, WA) in Nov 2024
Interview
Talked to a Hiring Manager on Linkedin and got the interview setup in a week. First I had the Phone Screen round which included a couple of LPs with a Leetcode medium style question using Trie DS followed by Resume Deep Dive and my PhD Dissertation.
After 3 days received an email for an on-site rounds. It was around 2 weeks between the PS and the on-site rounds. 7 rounds in total: Presentation on a topic of interest, ML Breadth, ML Depth, Coding, Bar Raiser, ML System Design, and System Design with the Hiring Manager.
Did well on all the rounds except for the coding. I had 4 back to back rounds on the 1st day without breaks and coding was the last of those, and my brain was exhausted talking thru all those rounds. My fault of not preparing mentally for this. But the interview experience was really great.
ML Sys Des: Design Alexa with none of the known tech
Sys Des: Design a System without any DL or Transformers ot LLMs based on my PhD Dissertation topic
Coding: Leetcode Medium
A lot of LPs. When I say "a lot", it's literally "a lot". Had notes for most of them prior to the interviews, but the interviewers delved so deep into each of those situations and answers that I felt overwhelmed for a few.
Prep:
Prepared answers for diff LPs
Coding on Leetcode for around 75 problems
System Design videos and blogs for prep on youtube
ML Breadth concepts and FAQs from diff prep blogs
Interview questions [1]
Question 1
Leetcode Medium
LPs
Resume Deep Dive
PhD Research
Standard ML questions on LR, L1 and L2 Regularization
One round ML . One round DSA. Ml had bredth and depth. It was tough. Prepare for ML from 100 days of ML. Best resource. Ml round had bredth and depth parts