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Amazon interview notes, page 68 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·Onsite - Product Sense / Strategy

May 2026
Amazon product or data role interview, one question about designing an experiment around a new matching algorithm for a ride-sharing context. Pretty open-ended and I wasn't totally sure what angle they wanted.
  • How would you design a test to evaluate whether a new rider-driver matching algorithm is actually performing better than the current one?

“I jumped straight into metrics before thinking about what 'better' even means, which was probably the wrong move.”

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Amazon·Software Engineer·Onsite - Behavioral / Leadership

May 2026
Interviewed for an EM role at Amazon, got asked about how I think about my broader impact on the world through engineering work. Pretty philosophical for what I expected to be a standard leadership screen.
  • As an engineering manager, how do you think about the impact your work has on the world beyond your team or company?

“I fumbled this a bit.”

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Amazon·Machine Learning Engineer·Onsite - Behavioral / Leadership

May 2026
Two behavioral questions for an MLE role at Amazon, both pretty standard leadership principle territory. Nothing technically deep but the ambiguity one tripped me up more than I expected.
  • Tell me about a time you had to make a decision or ship work when you didn't have all the information you needed. How did you move forward and what happened?
  • Describe a time you had to deliver something under a tight deadline. How did you figure out what to cut, what to keep, and how did you keep people in the loop?

“I had a decent story for this but fumbled the ending a bit.”

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Amazon·Software Engineer·Technical Phone Screen

May 2026
Amazon SWE SQL round focused entirely on window functions and CTEs, three questions ranging from easy to medium. Nothing crazy but you really do need to know your partition keys cold or it gets awkward fast.
  • Write a SQL query using CTEs and window functions (such as ROW_NUMBER, RANK, LAG, LEAD, or SUM OVER) to solve a data analysis problem given a table schema.

“Three questions total, easy to medium difficulty.”

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Amazon·Software Engineer·Technical Phone Screen

May 2026
Amazon SWE coding round, one question, stack-based simulation. Nothing fancy but it took me longer than I'd like to admit.
  • Given a list of logs from a single-threaded CPU, calculate the exclusive execution time for each function.

“Stack simulation problem.”

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Amazon·Software Engineer·Technical Phone Screen

May 2026
Amazon SWE interview with a backtracking/DP problem that looks straightforward but has enough edge cases to trip you up if you're not careful.
  • Given a string and a dictionary of valid words, insert spaces to produce all possible valid sentences where every word appears in the dictionary. Words can be reused, and the original character order must be preserved.

“My first instinct was pure recursion and I coded it up fast, felt good about it.”

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Amazon·Machine Learning Engineer·Technical Phone Screen

May 2026
Amazon ML Engineer interview, got a numpy-only implementation question on top-p sampling. Pretty technical, felt like a take-home style problem but was likely part of a coding round. No behavioral stuff from what I could tell.
  • Implement top-p (nucleus) sampling from scratch using only NumPy. Given raw logits, a cumulative probability threshold p, and a temperature parameter, return the index of a sampled token drawn from the renormalized nucleus distribution.

“This one took me a minute to get fully right.”

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Amazon·Software Engineer·Onsite - System Design / Architecture

May 2026
Amazon SWE interview with a system design question about building a file system. Not a lot of context to go on but it was clearly a design round.
  • Design a file system from scratch.

“This one has a lot of surface area and I'm not sure I scoped it well.”

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Amazon·Data Scientist·Technical Phone Screen

May 2026
Amazon Data Scientist technical phone screen with two meaty coding problems back to back. The first was a multiset intersection question with strict complexity constraints, and the second was a streaming top-K words problem with dense ranking. Pretty dense for a single session.
  • Implement a function that counts the size of the multiset intersection of two integer lists in O(n+m) time and O(min(n,m)) space, without sorting. Then implement a generator version that yields the overlapping elements without materializing the full result.
  • Build a streaming top-K words function that returns each word with its frequency and dense rank, handling ties lexicographically. Then discuss how you'd handle roughly a billion tokens with approximate methods.

“The O(n+m) constraint is what trips you up if you default to sorting.”

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Amazon·Software Engineer·Online Assessment (OA)

May 2026
Amazon SWE coding round where the main task was implementing a GPT model from scratch, including the attention mechanism, feedforward layers, and the full decoder stack. Pretty involved for what felt like a coding screen.
  • Implement a basic GPT model with MultiheadAttention, Feedforward, DecoderLayer, and GPT classes. The model should support forward propagation given parameters like vocabulary size, embedding dimension, number of layers, number of heads, dropout rate, and sequence length.

“I knew the high-level architecture but writing it out class by class under time pressure was rougher than expected.”

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