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Microsoft interview notes, page 3 of 60

FAANG / Big Tech

Most of these Microsoft write-ups come from Software Engineers (372), then Product Managers (124) and Machine Learning Engineers (53). The most reported rounds are the technical phone screen (255), the product sense round (111), the system design round (93) and the behavioral / leadership round (49).

597 interview notes · updated Oct 2026

Microsoft·Software Engineer·Onsite - Coding / Algorithms

Apr 2026
Round 4 at Microsoft for a software engineering role. Just one coding question, interval merging variant, nothing too exotic but you need to have the pattern down cold.
  • Given a list of intervals, output all overlapping intervals (a variant of the classic merge intervals problem).

“Sort first, then scan and track where intervals overlap.”

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Microsoft·Software Engineer·Technical Phone Screen

Apr 2026
Microsoft SWE interview with a graph problem that looked clean on the surface but had a few moving parts worth thinking through carefully.
  • Given an undirected graph where exactly one cycle exists, find the shortest distance from every node to the cycle. Nodes on the cycle should return 0.

“I knew BFS was involved but fumbled the first step a bit.”

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Microsoft·Machine Learning Engineer·Technical Phone Screen

Apr 2026
Microsoft ML Engineer interview, technical phone screen focused on NLP decoding algorithms. The main coding problem was a beam search implementation and the follow-up pushed into theoretical territory around length bias. Pretty deep for a phone screen.
  • Implement beam search decoding in Python. You're given a next-token probability simulator that takes the last token and returns a list of (token, probability) pairs. Maintain k candidate sequences, score them by cumulative log-probability, and stop when all beams hit end-of-sequence or a max length is reached. Return the final beams with their probabilities.
  • What is the main drawback of vanilla beam search, and how would you fix it?

“This took me longer to set up than I expected.”

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Microsoft·Software Engineer·Hiring Manager Screen

Apr 2026
Interviewed at Microsoft, got hit with a performance review hypothetical that I was not expecting at all. Felt more like a trap door than a warm-up question.
  • If we were having your first performance review today, what kind of feedback do you think I'd be giving you?

“Blanked for a second.”

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Microsoft·Software Engineer·Technical Phone Screen

Apr 2026
Microsoft SWE interview where they handed me a zip file with a small project and had me use an AI coding agent to find bugs and then add a feature for persisting in-memory data to disk. The twist was having to narrate and explain what the AI was doing as it went, which felt a bit like pair programming with a robot while someone watched over your shoulder.
  • You're given a zip file with a small project. Using an AI coding agent of your choice, identify bugs in the codebase and then implement a feature that saves in-memory data to disk. Walk the interviewer through what the AI is doing at each step.

“This was a weird format.”

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Microsoft·Software Engineer·Technical Phone Screen

Apr 2026
Microsoft SWE interview where they handed me a C++20 producer-consumer queue implementation and asked me to tear it apart. Pretty technical, no LeetCode, just real code review work.
  • You're given a C++20 producer-consumer message queue implementation using modern features like jthread, stop_token, concepts, and ranges. Do a full code review: find correctness bugs (race conditions, missing notifications, lost wake-ups, signed/unsigned issues), performance problems, and style issues. Propose and explain your fixes.

“This was the whole interview basically.”

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Microsoft·Product Manager·Hiring Manager Screen

Apr 2026
Interviewed for a PM role at Microsoft, got asked about concerns with the position itself which felt a bit unexpected mid-interview.
  • Do you have any concerns or reservations about this role?

“Stumbled on this one a bit.”

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Microsoft·Software Engineer·Technical Phone Screen

Apr 2026
ML foundations screen for an Applied Scientist role at Microsoft. Three topics, open-ended discussion format, felt more like a conversation than a grilling but that made it weirdly harder to know when to stop talking.
  • Walk me through the bias-variance trade-off and how it shows up in underfitting versus overfitting.
  • When would you use accuracy, precision, recall, or F1, and how does your answer change when classes are heavily imbalanced?
  • What is a confidence interval, how does it differ from a Bayesian credible interval, and how would you construct one for a classifier's accuracy?

“Felt solid here, probably the most rehearsed topic I had going in.”

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Microsoft·Software Engineer·Technical Phone Screen

Apr 2026
Had a Microsoft SWE interview that basically opened with a big picture question about AI. Not much else to go on, but it set a pretty conceptual tone from the start.
  • What are your thoughts on AI?

“Broad enough to go anywhere and that's exactly the problem.”

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Microsoft·Data Analyst·Technical Phone Screen

Apr 2026
Interviewed at Microsoft for what felt like a data analyst type role. One stats question, pretty conceptual, no coding involved. Short and a bit anticlimactic.
  • Why is standard deviation generally more useful than range when measuring the variability of a dataset?

“I knew the answer but fumbled the explanation a bit.”

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