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Microsoft interview notes, page 28 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·Product Manager·Onsite - Product Sense / Strategy

May 2026
Microsoft product sense interview, one question about designing something for cyclists. Short prompt, lots of room to go wrong.
  • Design a product for cyclists.

“Super open-ended and I kind of froze for a second trying to figure out which direction to go.”

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Microsoft·Software Engineer·Onsite - System Design / Architecture

May 2026
Microsoft data engineer interview, system design round. One question, pretty open-ended, and I spent way too long on the happy path before they started pushing on edge cases.
  • How would you design a system to ingest large volumes of JSON data from multiple S3 buckets?

“I jumped straight into the ingestion pipeline without asking enough about scale, frequency, or schema consistency across the buckets.”

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Microsoft·Software Engineer·Technical Phone Screen

May 2026
Microsoft SWE interview with a token management design problem. Pretty classic LeetCode-adjacent stuff but the TTL edge cases tripped me up more than I expected.
  • Design an authentication token manager that supports three operations given a fixed TTL: generating a new token with an expiry at currentTime + ttl, renewing a token only if it hasn't expired yet, and counting all currently unexpired tokens at a given time.

“I got the basic structure down fast, just a hashmap from tokenId to expiry time.”

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Microsoft·Software Engineer·Onsite - System Design / Architecture

May 2026
System design round at Microsoft for a software engineer role. The whole thing was one big question about designing a web crawler, and they kept pushing on scale and edge cases the entire time.
  • Design a large-scale web crawler that can discover, fetch, parse, and store web pages for use cases like search indexing or content analysis.

“This is one of those questions where you think you know it until you actually have to draw it out.”

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Microsoft·Software Engineer·Onsite - System Design / Architecture

May 2026
Microsoft system design round for a software engineering role. One meaty question about normalizing messy city name data, which sounds straightforward until you actually have to think through all the edge cases live.
  • Voting data contains city names in inconsistent formats like 'NYC', 'New York', and 'New York City'. How would you normalize these into canonical entities so votes aggregate correctly? Walk through both rules-based and ML-based approaches, how you'd pick similarity thresholds, what you'd do with ambiguous names like 'Springfield', and how you'd keep the mapping accurate over time.

“This one had more surface area than I expected.”

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Microsoft·Software Engineer·Technical Phone Screen

May 2026
Interviewed at Microsoft for a software engineering role and got a coding question around list manipulation. Pretty straightforward session, nothing too wild.
  • Given a list of integers, write code to find all numbers that appear an even number of times.

“Went with a frequency map, count occurrences, then filter.”

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Microsoft·Machine Learning Engineer·Onsite - Behavioral / Leadership

May 2026
Behavioral round for an ML Engineer role at Microsoft. Both questions were cross-team collaboration scenarios, which makes sense for the level but still felt like a lot of relationship management for what's supposed to be a technical role.
  • A team you depend on isn't treating your work as a priority. How do you keep your project moving?
  • Two teams have overlapping ownership of the same area. How do you resolve that without burning the relationship?

“This one I actually had a decent story for.”

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Microsoft·Machine Learning Engineer·Technical Phone Screen

May 2026
Microsoft ML Engineer interview where the main focus was a deep project walkthrough. You need to know your work cold because they will dig into every layer of it.
  • Walk me through a project you worked on: the problem, your approach, the key technical decisions you made, your specific contribution, the results, and what you took away from it.

“This sounds like a standard opener but it absolutely is not.”

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Microsoft·Software Engineer·Onsite - System Design / Architecture

May 2026
Microsoft interview for what seemed like a data center or infrastructure risk role. One big open-ended design question, no hints about scope, just kind of thrown in the deep end.
  • Design a comprehensive risk management plan for a data center.

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

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

May 2026
Microsoft ML Engineer system design round, one big open-ended question about building a RAG QA system for an enterprise knowledge base. The scope was massive and I kept second-guessing whether to go deeper on retrieval or spend more time on the agentic bits. Left feeling like I covered the surface of everything and the depth of nothing.
  • Design a RAG-based question-answering system for an enterprise knowledge base, where documents change over time, questions can be multi-step, and the system may call external tools like search or a calculator.

“This one sprawled in every direction and I never fully got my footing.”

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