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Microsoft

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 - Multi Round

Sep 2026
Went through three rounds of entry-level SDE interviews at Microsoft in the US, covering DSA, object-oriented design, system design, and CS fundamentals. Pretty well-rounded process, nothing too wild but the follow-ups kept things interesting.
  • Clone a linked list that has both next and random pointers.
  • What is the difference between authentication and authorization?
  • Explain the core principles of object-oriented programming.
  • Design a parking lot system, including classes, relationships, and how components interact.
  • Implement an LRU Cache from scratch.

“The base problem is manageable if you've seen it before.”

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Microsoft·Software Engineer·Online Assessment (OA)

Sep 2026
Internal transfer loop at Microsoft for an SDE role, same level. The process included a HackerRank OA, a system design component, and a behavioral round, though the OA ended up being cancelled before the candidate even sat it.
  • What is the typical format of a 75-minute HackerRank assessment at Microsoft, including number of questions, difficulty level, and whether MCQs or SQL appear?
  • Which algorithmic patterns come up most frequently in Microsoft coding assessments, and is focusing on hash maps, two pointers, sliding window, intervals, BFS/DFS, heaps, and stacks the right call?
  • How do hidden test cases and time limits work on HackerRank, and is partial credit actually given for incomplete solutions?
  • For an internal candidate, what depth is expected in a system design interview and is it more conversational or a structured whiteboard-style session?
  • In a behavioral or 'AA' round, can the conversation turn technical or is it purely leadership and values-based?

“I kept going back and forth on whether to expect two mediums or a mix with an easy thrown in.”

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Microsoft·Software Engineer·Online Assessment (OA)

Sep 2026
Applied for a Microsoft SWE summer internship and just wrapped up the OA. Two coding problems, one manageable and one that exposed some gaps in my algorithms prep. Now sitting here wondering if partial credit is enough to move forward.
  • Solve a coding problem at roughly easy difficulty level, passing all test cases.
  • Solve a harder coding problem requiring you to select the right data structure under time constraints.

“Got through this one clean.”

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Microsoft·Software Engineer·Online Assessment (OA)

Aug 2026
Ran into an AI-assisted coding problem on the Microsoft SWE intern HackerRank OA and started wondering what companies are actually evaluating when they watch how you use the AI tools.
  • What are companies actually looking for in how candidates use AI assistance during an online assessment?

“Second problem on the OA had AI assistance baked in and i genuinely had no idea if i was supposed to lean on it or treat it like a crutch to avoid.”

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Microsoft·Software Engineer·Online Assessment (OA)

Aug 2026
Took the Microsoft new grad OA and had a rough time. First problem clicked, second one did not, and now I'm sitting here wondering if partial credit is a thing.
  • Given an array, solve a problem using a prefix sum approach.
  • Solve a greedy array problem involving minimum and maximum constraints.

“Got this one fully.”

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Microsoft·Software Engineer·Onsite - Multi Round

Jul 2026
Went through three technical rounds at Microsoft for a senior role, 7 years in. DSA felt strong, system design was the weak link and I knew it walking out.
  • Design a scalable system, covering reliability and fault tolerance.
  • Solve an algorithmic problem, then discuss how your solution would hold up at scale.
  • Solve a second algorithmic problem with follow-up questions on scaling and edge cases.

“Covered scaling, reliability, and idempotency but completely blanked on caching.”

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Microsoft·Data Scientist·Technical Phone Screen

Jul 2026
Microsoft data scientist technical screen, heavy SQL focus with some tricky edge cases built into the schema. Three-part question that escalated from a delivery rate calculation to a scenario-based switching analysis. Felt like a reasonable challenge but part (c) was a curveball I wasn't fully ready for.
  • Given an Emails table and a Deliveries table, compute the proportion of emails delivered within 5 minutes of send time, grouped by provider and recipient domain, for emails sent in the last 7 days. Use the earliest delivered event, ignore spam_folder rows, and treat missing delivery records as undelivered. A bounce followed by a later delivery still counts if the delivered event falls within the 5-minute window.
  • Return all message IDs where the first observed delivery event was a bounce and a subsequent delivered event happened more than 5 minutes after the original send time. Include the lag in minutes between send time and the first delivered event.
  • For the ms.com domain over the same 7-day window, find the earliest calendar date where switching from Gmail to Outlook would have strictly improved deliverability. Base this on cumulative delivered-within-5-minutes rates up to and including each send date. Output the date and the cumulative rates that justify the switch.

“The spam_folder filter tripped me up first.”

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Microsoft·Product Manager·Onsite - System Design / Architecture

Jul 2026
Microsoft PM interview with a pretty technical system design angle. The question was about diagnosing a broken ML pipeline, which felt more like a data engineering interview than a product role, but I get why they ask it.
  • Your time-series ML pipeline has become unstable and prediction accuracy is degrading. Walk through how you'd diagnose the root cause across the data ingestion, feature generation, and model-serving layers. What evaluation framework, sampling strategy, and metrics would you use to quantify the regression? And what technical and process changes would you make to restore and maintain stability?

“This one is broad in a sneaky way.”

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Microsoft·Data Scientist·Onsite - Multi Round

Jul 2026
Microsoft Data Scientist interview that went deep on the full ML lifecycle, from problem framing all the way through post-launch monitoring. It was a lot to cover in one session and I felt like I was speed-running my entire career.
  • Walk me through an ML project you owned end-to-end: how did you frame the problem, define success metrics tied to business KPIs, and get alignment across PM, Engineering, and Legal?
  • How did you handle data sourcing and privacy constraints in that project?
  • How did you choose your model and evaluate it both offline and online? What did your experiment design look like?
  • Tell me about a time a PM strongly pushed back on your recommendation. How did you change their mind, and what was the measurable outcome?
  • Describe a failure in an ML project: what broke, what did you change, and how did you make the process more reproducible afterward?
  • How do you approach fairness and ethical considerations in a model when you're under real time pressure to ship?

“This is the kind of question that sounds manageable until you realize they want specifics on every single handoff.”

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Microsoft·Software Engineer·Technical Phone Screen

Jul 2026
Phone screen for a Software Engineer role at Microsoft where they handed me an AI-written URL shortener and asked me to tear it apart. Decent question, though I'd say the follow-ups were where it got genuinely hard.
  • You're given an AI-generated in-memory URL shortener implementation. Walk through the bugs and correctness issues in both the shorten and resolve methods, explain why each is a problem, and describe how you'd fix them.
  • How would you write a unit test that deterministically reproduces the collision bug in the code generator?
  • If this service had to run across multiple processes or servers, which assumptions in the current in-memory design break and what would you change?
  • How would you make the code generation both collision-resistant and unguessable at the same time?
  • If the url_to_code reverse map was removed entirely, what behavior changes and does that fix or remove any of the existing bugs?

“The collision bug in shorten is the obvious one, and I spotted it pretty quick.”

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Microsoft interview FAQ

What rounds are in the Microsoft interview?

Candidates most often report a technical phone screen (255 write-ups), a product sense round (111), a system design round (93) and a behavioral / leadership round (49).

What does the Microsoft technical phone screen cover?

Across 255 technical phone screen write-ups, the most tagged question topics are Technical Trade-offs (255 questions), Algorithms & Data Structures (239) and System Design (111).

What is asked in the Microsoft product sense round?

Across 111 product sense write-ups, the most tagged question topics are Product Strategy (89 questions), Product Sense & Ideation (88) and Adaptability & Ambiguity (37).