Microsoft Interview Questions

Microsoft Interview Questions

Practice 213 real Microsoft interview questions for 2026. Covers all top categories — Coding & Algorithms, Behavioral & Leadership, System Design, Machine Learning, ML System Design — across Software Engineer, Data Scientist, Machine Learning Engineer, Product Manager, Technical Program Manager roles. Real questions from actual interviews with detailed solutions. Microsoft interview questions on this page focus heavily on coding and design: expect algorithmic problems, implementation correctness and complexity tradeoffs, and end-to-end system thinking during on-site loops. Interview preparation should combine timed coding drills, low-level and distributed design sketches, and polished STAR narratives that show impact and collaboration. For Software Engineers you’ll see recurring themes like versioned key-value stores, secure Copilot APIs, RAG ranking and retrieval pipelines, CSV/query engines, calendar and meeting-optimizer systems, URL shorteners, and memory/Java/Python management. Data Scientist questions concentrate on SQL aggregation/top-earner queries, classifier design and evaluation, estimating impact without A/B tests, SHAP and precision–recall analysis. Machine Learning Engineers face top-K/top-elements, LLM data quality checks, model selection, caching/merge interval problems, and RAG systems with agentic tools. Product roles emphasize customer obsession, cross-team influence, enterprise process tooling, metrics, and ML pipeline stability.

213 Questions 1 Company08.03.2026
Showing 20 results
Role
Microsoft logo
Microsoft
Medium
Software Engineer Locked

Find the Bugs in an AI-Generated URL Shortener

This question evaluates a candidate's ability to review AI-generated code for correctness, consistency, and robustness rather than write code from scr...

Software Engineering Fundamentals
41
1
281 people solved
Jun 12, 2026
Microsoft logo
Microsoft
Medium
Software Engineer

Minimize Fuel Cost Across Cities

Minimize Fuel Cost Across Cities Problem Hackerland has g_nodes cities numbered from 1 through g_nodes and bidirectional roads. Road i connects g_from...

Coding & Algorithms
0
0
10 people solved
Aug 3, 2026
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Microsoft
Medium
Software EngineerSenior+ Locked

Design a Distributed Key-Value Store

This system design question evaluates the ability to architect a horizontally scalable distributed key-value store, covering data partitioning, replic...

System Design
33
0
234 people solved
Jun 11, 2026
Microsoft logo
Microsoft
Medium
Data ScientistSenior+ AI

Build and Defend a Baseline Model from a CSV

You receive a CSV during a live interview and are asked to build a useful predictive model. You may use code-completion or agent tools, but you must d...

Machine Learning
5
0
50 people solved
Jun 29, 2026
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Microsoft
Medium
Software Engineer Locked

Design a URL Shortener (High-Level and Low-Level Design)

This question evaluates the ability to design a large-scale distributed system, covering both high-level architecture and low-level implementation det...

System Design
4
0
65 people solved
Jun 12, 2026
Microsoft logo
Microsoft
Medium
Software Engineer Locked

Design a To-Do List Service (CRUD, Auth, Rate Limiting, Caching & API Versioning)

This system design question evaluates practical full-stack architectural thinking across REST API design, authentication, rate limiting, and caching i...

System Design
10
0
142 people solved
Jun 11, 2026
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Microsoft
Medium
Data ScientistSenior+

Evaluate a Product Change That Adds More User Options

A product team wants to add more options to an existing user flow. Design an experiment to determine whether the change improves the product, and expl...

Analytics & Experimentation
2
0
23 people solved
Jun 29, 2026
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Microsoft
Medium
Data ScientistSenior+

Analyze an AI Product Pilot and Recommend Whether to Expand It

An AI product has been tested with a limited group of pilot users. The product team asks whether it should expand access. Describe how you would analy...

Analytics & Experimentation
1
0
21 people solved
Jun 29, 2026
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Microsoft
Medium
Software EngineerSenior+ Locked

Externally Sort a 500 GB CSV by One Column with 16 GB of RAM

This question evaluates a candidate's ability to design an external merge sort for data far larger than available memory, a core systems design skill....

System Design
6
0
49 people solved
Jun 11, 2026
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Microsoft
Medium
Data Scientist

Compute the Product of an Array Except Self

The interview report preserved the input-output example but not every original restriction. The following is a self-contained version of the reported ...

Coding & Algorithms
8
1
59 people solved
May 4, 2026
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Microsoft
Medium
Data Scientist

Design Product-Description Content Moderation at Marketplace Scale

Prompt Design a system that detects and handles inappropriate text in seller-uploaded product descriptions for a marketplace containing billions of pr...

ML System Design
3
0
41 people solved
May 4, 2026
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Microsoft
Medium
Software EngineerSenior+ Locked

Design a Metrics Ingestion Pipeline

This question evaluates a candidate's ability to design a large-scale distributed system for ingesting time-series metrics at high throughput. It test...

System Design
5
0
46 people solved
Jun 11, 2026
Microsoft logo
Microsoft
Medium
Software Engineer

Design a Secure Copilot API

Design a secure API for an enterprise AI copilot product. The product serves many independent organizations (tenants). Authenticated end users send pr...

System Design
18
0
314 people solved
Apr 6, 2026
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Microsoft
Medium
Machine Learning EngineerIntern

Design a RAG system with agentic tools

Design a Retrieval-Augmented Generation (RAG) question-answering system for an enterprise knowledge base. Requirements: - Users ask natural-language q...

ML System Design
13
0
192 people solved
Feb 9, 2026
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Microsoft
Easy
Software Engineer

Solve four classic algorithm problems

You are given four independent coding tasks. For each task, implement the required function. --- Problem 1: Zigzag level-order traversal of a binary t...

Coding & Algorithms
18
0
152 people solved
Nov 30, 2025
Microsoft logo
Microsoft
Medium
Software Engineer

Design A Scalable Web Crawler

Design a scalable web crawler that discovers, fetches, parses, and stores web pages for downstream use such as search indexing or content analysis. Yo...

System Design
10
0
86 people solved
Apr 18, 2026
Microsoft logo
Microsoft
Medium
Software Engineer Locked

Design Chatbot Personalization Memory

This question evaluates competency in designing per-user chatbot memory systems, including data modeling for durable memories, retrieval-augmented gen...

ML System Design
13
0
123 people solved
May 7, 2026
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Microsoft
Medium
Data Scientist

Choose Classification Metrics Under Asymmetric Costs

You are evaluating a binary classification model for a business problem. Explain how to use a confusion matrix to compute and interpret: - precision, ...

Statistics & Math
11
0
123 people solved
Feb 25, 2026
Microsoft logo
Microsoft
Medium
Software Engineer

Design A Low-Latency Product Price Update API

Design an API and serving system for product prices. Each product price is updated at most once every 24 hours, but the product launch page needs low-...

System Design
2
0
26 people solved
Apr 24, 2026
Microsoft logo
Microsoft
Medium
Software EngineerSenior+

Design User Re-engagement Notifications

Design a re-engagement system for an AI assistant product. The system should support at least two use cases: 1. Send relevant notifications to inactiv...

System Design
9
0
80 people solved
Apr 10, 2026

Frequently Asked Questions

How hard are Microsoft interview questions for the roles covered on this page?
Microsoft interview questions are rigorous and vary by role and level: expect strong emphasis on coding and algorithmic problem solving for Software Engineer roles, systems and scalability thinking for senior engineers, and a mix of coding, statistics and experimental design for Data Scientist and Machine Learning Engineer roles. Product and program roles focus more on product judgment, execution and cross‑team influence. Difficulty scales with seniority and team scope, and many interviews test production readiness, tradeoff reasoning and measurable impact rather than only theoretical knowledge.
What does the typical Microsoft interview process look like and where do these question types appear?
The common flow starts with a recruiter screen, a technical phone/video screen, then a virtual or onsite loop of four to five interviews and sometimes a final 'As Appropriate' leadership review. Coding & Algorithms rounds predominately assess Software Engineers, System Design appears more for mid/senior levels, Machine Learning and ML System Design rounds target MLEs and Data Scientists, and Behavioral & Leadership evaluations run in every loop. Interview timelines typically span several weeks; the exact mix depends on role, level and the specific team’s product priorities.
How long should I prepare before interviewing at Microsoft and how should I structure that time?
Plan preparation by role: engineers often need six to twelve weeks of focused work, while Data Scientists and MLEs can be ready in four to eight weeks if they balance coding, statistics and model evaluation practice. Product and TPM candidates usually need two to six weeks to assemble clear case studies and practice stakeholder narratives. Start with fundamentals and timed problem practice, add system design and production-readiness review mid-plan, then run full mock loops in the final weeks. Include deliberate practice on explaining tradeoffs, telemetry and impact throughout your preparation.
What are the key technical themes to prioritize for Microsoft interviews by position?
Software Engineers: recurring themes include distributed storage and versioned key-value design, graph algorithms and 'tour' style problems, parser/tokenizer and CSV/query-engine implementation, memory/efficiency considerations and practical services like URL shorteners and calendaring. Data Scientists: focus on metric selection under asymmetric costs, SHAP/feature‑attribution, precision–recall analysis, experiment alternatives to A/B and SQL-style data extraction and aggregation. Machine Learning Engineers: expect LLM/RAG system design, quality checks for labeled/LLM data, precision/recall computation from flaky APIs, caching/merge-interval patterns and rigorous ablation and regularization analysis. Product roles: enterprise process flows, ML pipeline stability and clear north-star metrics.
What standout tips and common pitfalls should I know when preparing for Microsoft interviews?
Standout tips: write production-quality code with clear edge-case handling and complexity justification, explain monitoring, rollout and rollback plans for designs, quantify business impact and use telemetry when describing ML work, and practice crisp STAR stories that show ownership and collaboration. Common pitfalls: solving only the toy version of a problem, ignoring performance or reliability tradeoffs, failing to ask clarifying questions, giving vague evaluation metrics or disregarding data bias and safety in ML discussions, and not tying technical choices back to customer or business outcomes.

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