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Microsoft interview notes, page 55 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·Machine Learning Engineer·Onsite - System Design / Architecture

Jul 2026
System design round at Microsoft for an ML Engineer role. Just one question but it took the whole session and there's more to it than the name suggests.
  • Design a product search system.

“Spent probably too long on the query understanding layer and not enough on ranking.”

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Microsoft·Software Engineer·Technical Phone Screen

Jul 2026
Microsoft software engineer round that skipped the leetcode grind entirely and went straight into backend design territory. Two meaty questions back to back, both requiring you to actually think about how software gets built and shipped in the real world.
  • You need to add new business logic to an existing backend service using object-oriented design. How do you identify the core domain objects, assign responsibilities, separate orchestration from business rules, and keep the code testable and extensible?
  • You need to change a public API that existing clients already depend on. Walk through how you'd ship that change safely, covering backward compatibility, versioning strategy, testing, rollout approach, monitoring, and client communication.

“This one took me a minute to get traction on.”

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Microsoft·Product Manager·Onsite - Product Sense / Strategy

Jul 2026
PM interview at Microsoft with a single pricing strategy question. Not much to report on process or outcome, but the question itself was pretty meaty.
  • Should Microsoft change its pricing models?

“Bigger than it looks.”

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Microsoft·Software Engineer·Onsite - System Design / Architecture

Jul 2026
System design round at Microsoft for a software engineer role, focused entirely on building a large-scale metrics ingestion pipeline. The problem was meaty and covered a lot of ground, from ingest throughput to failure modes to storage layout. Felt like the kind of question where you could spend three hours on it and still leave things on the table.
  • Design a metrics ingestion pipeline for a large engineering organization where tens of thousands of hosts emit millions of data points per second. The system needs to collect, aggregate, store, and serve metrics to dashboards and alerting, and it has to hold up under failure.
  • What clarifying questions would you ask before diving into the design? Things like push vs pull, acceptable latency, and what happens when the pipeline is overloaded.
  • Walk through what happens when different components of the pipeline fail or get overloaded. How does the system degrade gracefully without taking down the services that are emitting metrics?
  • A bad deployment starts emitting a label whose value is a unique per-request ID, causing cardinality to explode by 100x. How do you detect and contain it without dropping metrics from healthy services?
  • How do you ensure counter semantics are correct across agent restarts, network retries, and duplicate deliveries?
  • How would you serve a dashboard query that spans the full 13-month retention window quickly, given that older data is stored at coarser resolution?
  • Where could ML or AI genuinely help operate this kind of pipeline, and what are the risks of relying on it?

“This was the main question and it ate the whole session.”

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Microsoft·Technical Program Manager·Technical Phone Screen

Jul 2026
Brief TPM screen at Microsoft, just one question about tooling experience.
  • What tools have you used in your work as a TPM?

“Pretty standard opener.”

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Microsoft·Software Engineer·Onsite - Behavioral / Leadership

Jul 2026
Behavioral round at Microsoft for a software engineer role. One hour, one or two questions total, but the interviewer digs hard into every answer so don't expect to coast on a vague story.
  • Walk me through a situation where you had to make a significant technical or project decision. What was your role, what did you actually do, and how did you measure whether it worked?

“The question itself sounds normal until they start drilling.”

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Microsoft·Software Engineer·Onsite - System Design / Architecture

Jul 2026
Microsoft system design round for a software engineer role. Started with some fundamentals then moved into designing an API gateway. Nothing too wild but it covered more ground than I expected.
  • How does a hashmap work internally?
  • What are the fundamentals of database design you should consider when building a scalable system?
  • Design an API gateway.

“Pretty basic but they wanted specifics, not just 'key-value pairs'.”

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Microsoft·Product Manager·Onsite - Product Sense / Strategy

Jul 2026
Interviewed at Microsoft for what seemed like a product or strategy role. Single question about VR in education, not much else to go on.
  • How would you use VR to improve education?

“Broad question with a lot of surface area.”

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Microsoft·Software Engineer·Onsite - System Design / Architecture

Jul 2026
System design round at Microsoft for a software engineering role. The whole session was basically one big question about building a ticket booking platform at scale, and they really pushed on the details rather than letting you stay high-level.
  • Design a large-scale online ticket booking platform similar to Ticketmaster. Walk through how you'd handle browsing events, viewing seat maps, holding and purchasing seats, and delivering tickets to users.
  • How would you prevent double-booking when millions of users are trying to grab the same seats at the same time?
  • How would you design a virtual waiting room to handle fairness when a high-demand event goes on sale?
  • Walk me through how you'd handle payment idempotency and the cancellation and refund flow in this system.

“I started with the usual API and data model stuff but they pushed me pretty fast toward the hard parts.”

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Microsoft·Machine Learning Engineer·Technical Phone Screen

Jul 2026
Microsoft MLE interview that was basically a stats and experimentation deep-dive with a short Python debugging exercise tacked on at the end. Pretty business-focused, not the leetcode grind I was expecting.
  • How would you design an A/B test for a product change, and what considerations would guide your setup?
  • How do you choose the appropriate statistical test for a given experiment?
  • What is a p-value and how would you explain it to a non-technical stakeholder making a product decision?
  • How do you handle the multiple comparisons problem when running several tests simultaneously?
  • Walk me through how you would estimate the required sample size for an experiment.
  • How do you think about the tradeoff between false positives and false negatives when making a product launch decision?
  • You're given a short Python snippet with bugs. Find them, fix them, and explain your reasoning.

“This was basically the anchor question the whole conversation orbited around.”

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