← Back to Directory

Amazon interview notes, page 40 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·Recruiter / HR Screen

May 2026
Interviewed at Amazon for what seemed like a recruiting or HR screening role. Just one question came up around resume screening criteria, nothing too intense.
  • What criteria do you prioritize when screening resumes?

“Pretty standard for a recruiting role but I still stumbled a bit trying to sound structured without being too rigid.”

View Post

Amazon·Software Engineer·Onsite - Coding / Algorithms

May 2026
Amazon SWE coding round with a string manipulation problem that's trickier than it looks on the surface. The binary search angle took me a while to see.
  • You're given a string S, an offset array O that defines the order in which characters get replaced by '*', and an integer M. Each round you replace S[O[i]] with '*'. What's the minimum number of rounds required so that the number of substrings containing at least one '*' reaches at least M?

“My first instinct was to simulate it round by round and count substrings each time, which obviously blows up for large inputs.”

View Post

Amazon·Machine Learning Engineer·Onsite - System Design / Architecture

May 2026
System design round at Amazon for an ML engineer role. The whole question was about building a validation pipeline for LLMs, covering everything from tensor-level checks to human review. Pretty broad scope for one question.
  • Design an end-to-end quality validation system for a team that trains and serves large language models. The system should automatically evaluate correctness, safety, and regression risk across new model versions and live production responses.

“This one sprawled fast.”

View Post

Amazon·Data Scientist·Technical Phone Screen

May 2026
SQL technical screen for a Data Scientist role at Amazon. One question, music app themed, friend recommendation via listening overlap. Felt manageable on the surface but the edge cases pile up fast.
  • Given a table of user song listens and a table of existing friendships, write a SQL query to recommend new friend pairs who listened to more than 3 of the same songs on the same day, excluding pairs who are already friends.

“The core join isn't bad but the unordered pair thing tripped me up for a minute.”

View Post

Amazon·Research Scientist·Technical Phone Screen

May 2026
Phone screen for an Applied Scientist intern role at Amazon, mixed coding and concept questions. The main coding ask was implementing InfoNCE from scratch in PyTorch, which sounds manageable until you're staring at a blank file under time pressure.
  • Implement the symmetric InfoNCE contrastive loss in PyTorch from scratch, given query and key embeddings of shape (B, D) where positive pairs are along the diagonal.
  • How does the temperature parameter affect gradients in the InfoNCE loss, and what are the practical tradeoffs of setting it too low or too high?
  • What happens to the InfoNCE loss when the batch size is very small, and how does MoCo address this?
  • Explain the difference between the SimCLR and MoCo loss formulations and why MoCo uses a separate momentum encoder for the key branch.

“This is the kind of question where you think you know it and then your hands just stop.”

View Post

Amazon·Software Engineer·Technical Phone Screen

May 2026
Amazon SWE coding round, one question the whole time. Pretty standard algorithmic problem but they wanted complexity analysis too, which I almost forgot to walk through properly.
  • Given an ASCII string, reorder its characters by descending frequency. For ties in frequency, sort those characters in ascending lexicographic order. Return the resulting string, and analyze the time and space complexity of your solution.

“I knew the sorting logic pretty quickly, frequency map then sort, but the tie-breaking part tripped me up for a minute.”

View Post

Amazon·Software Engineer·Onsite - Behavioral / Leadership

May 2026
Behavioral screen for a data engineer role at Amazon. Just one question but it's the kind that trips people up if you haven't thought about it beforehand.
  • Tell me about a skill you recently learned.

“Classic Amazon leadership principles bait.”

View Post

Amazon·Software Engineer·Online Assessment (OA)

May 2026
Got an Amazon SWE coding round with a word break problem. Pretty classic backtracking/DP territory but the 'return all sentences' variant tripped me up a bit compared to the simpler yes/no version.
  • Given a string and a word dictionary, insert spaces into the string to form all possible valid sentences where every word exists in the dictionary. Words can be reused. Return all valid sentences.

“My first instinct was pure recursion and I coded it up fine for small inputs, but I hadn't thought about the overlapping subproblems until I was almost done.”

View Post

Amazon·Technical Program Manager·Hiring Manager Screen

May 2026
TPM interview at Amazon with at least one question about standing up a program from nothing. Pretty open-ended, which I wasn't totally prepared for.
  • How would you go about launching a brand new program from the ground up?

“I rambled a bit on this one.”

View Post

Amazon·Software Engineer·Technical Phone Screen

May 2026
Amazon SWE coding round with a greedy string problem. Pretty focused session, just the one question but they pushed on the reasoning behind the approach.
  • You're given a string with '?' placeholders, where each placeholder position has an associated overhead cost depending on which character you place there. Replace all '?' characters to minimize the total overhead. What's your approach and what's the minimum total cost?

“Greedy felt obvious to me once I read it twice.”

View Post