← Back to Directory

Amazon interview notes, page 85 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·Software Engineer·Onsite - System Design / Architecture

May 2026
Amazon system design round, one question, no fluff. They asked me to design Prime Video and just kind of let me run with it.
  • Design a video streaming platform like Prime Video.

“Spent the first few minutes trying to scope it properly because the question is massive.”

View Post

Amazon·Software Engineer·Technical Phone Screen

May 2026
Three coding problems at Amazon for a software engineer role. Nothing too wild but the tree one had a subtle edge case that I fumbled a bit, and the third problem took me longer to see the right approach than I'd like to admit.
  • Given n distinct students with unique IDs, return all possible ways to arrange them in a line. Follow-up: return all distinct circular arrangements, where rotations count as the same.
  • Given a binary tree and two target nodes, classify their relationship: return 'siblings' if they share a parent, 'cousins' if they're at the same depth with different parents, or 'others' in all remaining cases including if either node is missing from the tree.
  • Given an unsorted integer array and a positive integer k, find the longest subsequence of strictly increasing distinct values where every consecutive pair differs by less than k.

“The linear part is just generating all permutations, pretty standard.”

View Post

Amazon·Machine Learning Engineer·Technical Phone Screen

May 2026
Amazon ML engineer interview that was pretty much a deep dive into linear regression from scratch. One question, but they really wanted you to go all the way from loss definition down to SGD pitfalls, so it took a while.
  • Given a dataset of 1D samples, fit a linear model by minimizing MSE. Walk through defining the loss, deriving gradients for both parameters via backprop-style reasoning, implementing SGD training with initialization and update rules, and discuss pitfalls like scaling and divergence.

“This looks like a textbook question until you realize they want the full chain: write out the MSE, differentiate with respect to both slope and intercept, then actually talk through SGD like you'd implement it, not just recite the update rule.”

View Post

Amazon·Software Engineer·Hiring Manager Screen

May 2026
Behavioral interview for a Business Intelligence Engineer role at Amazon. The manager went pretty deep on each answer, which I wasn't fully expecting, but the whole thing felt pretty relaxed and low-pressure. Still waiting to hear back.
  • Tell me about a time you took on work that was outside your defined responsibilities.

“Went into this one feeling okay but the follow-up questions got pretty granular fast.”

View Post

Amazon·Technical Program Manager·Onsite - Behavioral / Leadership

May 2026
Behavioral round for a TPM role at Amazon, pretty much what you'd expect: leadership principles front and center.
  • Tell me about a time you went beyond what a customer expected and delivered something more than they asked for.

“I had a story ready but halfway through I realized it was more about hitting a deadline than actually exceeding expectations.”

View Post

Amazon·Software Engineer·Technical Phone Screen

May 2026
Amazon SWE coding round, pretty standard stuff. Got a frequency-counting problem and had to return the top k most frequent elements from an array.
  • Given an array of integers, return the k most frequent elements.

“Classic bucket sort or heap problem.”

View Post

Amazon·Software Engineer·Onsite - System Design / Architecture

May 2026
Amazon system design round for a software engineering role. The whole session was basically one big design problem with a follow-up that added real complexity, and I left feeling like I got through it but not cleanly.
  • Design a package installer system that handles dependency resolution, installs transitive dependencies in a valid order, detects cycles, and gracefully handles packages that are already installed.
  • Extend your design so that each package carries a payload that gets passed into its install hook. How do you thread these payloads through the dependency graph?

“I started with the data model which felt right, packages with versions and a dependency list, pretty standard graph setup.”

View Post

Amazon·Product Manager·Onsite - Cross-functional / Panel

May 2026
Amazon PM interview, got asked about cross-functional collaboration. Pretty thin on details but the question itself is one you should have a real answer for.
  • How do you work with engineering and data science teams as a PM?

“This sounds routine but it's easy to give a fluffy answer that doesn't land.”

View Post

Amazon·Machine Learning Engineer·Technical Phone Screen

May 2026
Amazon ML Engineer interview focused heavily on LLM fundamentals, covering everything from tokenization internals to inference optimization and safety. A lot of ground to cover and the breadth of it was a bit exhausting.
  • How does subword tokenization work, and why do modern LLMs use it instead of word-level or character-level approaches?
  • Explain how self-attention works and why its computational cost scales quadratically. What approaches exist to reduce that cost?
  • What are the differences between pretraining, instruction tuning, and alignment techniques like RLHF or DPO?
  • Describe how you would design a RAG system, including how you'd handle indexing, chunking strategy, embedding choices, and the tradeoff between sparse and dense retrieval.
  • How do you decide between prompting, fine-tuning, and parameter-efficient methods like adapters for a given use case?
  • What techniques do you use to optimize LLM inference for low latency, specifically around quantization, KV caching, and batching?
  • How do you evaluate LLM outputs, and what strategies do you use to reduce hallucinations and manage safety risks?

“Walked through BPE: start with characters, merge the most frequent adjacent pairs iteratively until you hit your vocab size.”

View Post

Amazon·Software Engineer·Online Assessment (OA)

May 2026
Amazon SWE coding round with one problem that looks simple on the surface but has enough edge cases to trip you up if you're not careful. The no-built-in-date-functions constraint is the whole point.
  • Given a date string in 'YYYY-MM-DD' format, write a function that returns how many days have passed from that date to today. You cannot use any built-in date or time libraries.

“The constraint is what makes this annoying.”

View Post