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Amazon interview notes, page 108 of 159

FAANG / Big Tech

Most of these Amazon write-ups come from Software Engineers (1,092), then Data Scientists (182) and Product Managers (165). The most reported rounds are the technical phone screen (618), the behavioral / leadership round (309), the online assessment (228) and the system design round (159).

1581 interview notes · updated Oct 2026

Amazon·Product Manager·Hiring Manager Screen

Jun 2026
Short Amazon interview question about competitive positioning, not much else to go on.
  • Do you see Amazon and Intuit as competitors?

“Tricky because the obvious answer is 'not really' but then you start thinking about small business financial tools, AWS integrations, Amazon's lending products...”

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Amazon·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Amazon ML Engineer interview that went deep on project internals, specifically around training dynamics. They really wanted to know if you understood the 'why' behind your design choices, not just what you used.
  • Walk through your ML/DL project in detail. Which learning rate scheduler did you use and what was your reasoning for choosing it over the alternatives?
  • Explain how gradient clipping works. What is the difference between norm-based and value-based clipping, and in what situations do you actually need it?

“This is where I fumbled a bit.”

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Amazon·Data Scientist·Technical Phone Screen

Jun 2026
Amazon data science interview with a deep causal inference question that felt more like a research design exam than a typical DS screen. The level of technical detail expected was pretty intense.
  • Walk through how you would estimate the average treatment effect of sending a first reminder notification on customer satisfaction scores using Double Machine Learning, including how you'd incorporate text from user addresses into your feature set.
  • How would you check for overlap or positivity violations in this setup, and what would you do if you found them?
  • How would you test sensitivity to unobserved confounding, and how would you handle subgroup analyses across device and channel while controlling for false discovery rate?
  • How would you validate that the text features derived from addresses are actually contributing meaningfully, and how would you handle geographic privacy and fairness concerns?

“This was a beast of a question.”

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Amazon·Software Engineer·Technical Phone Screen

Jun 2026
Amazon SWE interview with a data structure design question that seemed straightforward at first but had a few wrinkles worth thinking through carefully. One question, focused on system design and complexity analysis.
  • Design a data structure that accepts login events (user_id, timestamp) and can return the user with the earliest login among users who have logged in exactly once. Walk through insert and query complexity, and explain how the structure needs to handle a user logging in a second time.

“The 'exactly once' constraint is what makes this interesting.”

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Amazon·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Amazon system design round for a software engineer role, one big OOP question that took the whole session. The question was meaty enough that I kept second-guessing whether I was going too deep on modeling or not deep enough on the operational logic.
  • Design a credit card system using object-oriented principles. Model the core entities (Cardholder, Card, Account, Transaction, Statement) and their relationships, and support operations like issuing cards, authorizing charges, recording payments, generating monthly statements, and tracking transaction history. Also discuss how you'd handle declined transactions and over-limit scenarios.

“Started with the entities and drew out relationships pretty confidently, Cardholder owns an Account, Account has many Cards, Cards generate Transactions, Transactions roll up into Statements.”

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Amazon·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
PM interview at Amazon, single question about expanding into a new market. Pretty open-ended, no hints on scope or constraints, just kind of thrown at you.
  • How would you launch Amazon in Nigeria?

“I froze for a second because the question is so wide open.”

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Amazon·Software Engineer·Technical Phone Screen

Jun 2026
Amazon SWE coding round, one question on multi-source BFS. Short and focused, nothing else to report.
  • Solve a problem using multi-source BFS (breadth-first search from multiple starting nodes simultaneously).

“Classic multi-source BFS setup.”

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Amazon·Software Engineer·Online Assessment (OA)

Jun 2026
Amazon OA for a SWE role. One algorithmic problem about counting subarrays, pretty standard sliding window territory but easy to overthink if you're not warmed up.
  • Given an array of server workloads and an integer difference, count how many contiguous subarrays have a max-min difference exactly equal to that integer.

“The example with [2,4,6] and k=2 gives 2, which checks out (subarrays [2,4] and [4,6]).”

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Amazon·Software Engineer·Technical Phone Screen

Jun 2026
Amazon SWE coding round, one algorithmic problem that looked manageable until I started thinking about the neighbor-update logic. Took a while to land on the right data structure combo.
  • You have an array treated as a circular sequence. Each round, pick the smallest remaining element, add it to a running total, then remove it and both of its current neighbors. Repeat until nothing is left. Return the total. What's your approach and what's the time complexity?

“I got the greedy logic pretty fast, smallest element each round, sure.”

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Amazon·Product Manager·Onsite - Behavioral / Leadership

Jun 2026
Amazon PM loop, got hit with a project pivot question that I thought I handled okay but honestly left the room second-guessing myself.
  • Describe a situation where you had to change the direction of a project that was already most of the way through completion.

“I fumbled the opener.”

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