Microsoft interview questions

Showing 31–60 of 252 results

• Compute product of array except selfHard

  This problem tests your ability to manipulate array prefixes and suffixes to compute aggregate values efficiently without using the division operator, while handling constraints like modular arithmetic.

  MicrosoftSoftware EngineerCoding & AlgorithmsOnline Assessment
• Compute shortest path in cyclic graphMedium

  This question tests the ability to implement a shortest-path algorithm in a directed graph that may contain cycles, specifically evaluating the selection between Dijkstra's algorithm and Bellman-Ford based on edge weight constraints.

  MicrosoftSoftware EngineerCoding & AlgorithmsTechnical Screen
• Compute sum of longest positive subarrayMedium

  Compute sum of longest positive subarray evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  MicrosoftSoftware EngineerCoding & AlgorithmsTechnical Screen
• Convert a Hexadecimal Address to Dotted IPv4Medium

  Convert an eight-digit hexadecimal address to network-order dotted IPv4 with strict validation, optional prefixes, and correct high-bit handling.

  MicrosoftSoftware EngineerCoding & AlgorithmsOnsite
• Count Binary Substrings with Two Equal BlocksMedium

  Tests string traversal, run-length grouping, and recognizing how adjacent homogeneous blocks contribute to valid balanced substrings.

  MicrosoftSoftware EngineerCoding & AlgorithmsOnline Assessment
• Count Non-Decreasing Arrays with Prescribed Digit SumsHard

  Count non-decreasing arrays whose values are at most 5000 and match specified decimal digit sums, returning the total modulo 1000000007.

  MicrosoftSoftware EngineerCoding & AlgorithmsOnline Assessment
• Count Occurrences of Each Suffix MaximumMedium

  This problem tests your ability to use a monotonic stack and a hash map (or frequency array) to efficiently answer suffix queries about the occurrences of the maximum value.

  MicrosoftSoftware EngineerCoding & AlgorithmsTechnical Screen
• Count integer pairs satisfying 1/x + 1/y = 1/NMedium

  This question evaluates understanding of number theory and algorithmic problem-solving, focusing on Diophantine equation manipulation, divisor counting, and translating algebraic constraints into combinatorial counts.

  MicrosoftSoftware EngineerCoding & AlgorithmsOnline Assessment
• Count k for consecutive-sum generatorMedium

  This question evaluates number-theoretic reasoning and understanding of arithmetic progressions, focusing on how sums of consecutive positive integers can be characterized and counted.

  MicrosoftSoftware EngineerCoding & AlgorithmsTechnical Screen
• Count non-decreasing arrays by digit sumsMedium

  This question evaluates combinatorics and constrained counting skills, including reasoning about digit-sum properties, monotonic sequences, modular arithmetic, and efficient algorithm design within the Coding & Algorithms domain.

  MicrosoftSoftware EngineerCoding & AlgorithmsTechnical Screen
• Count the Separate Land Regions in a Binary Grid MapMedium

  A coding exercise that counts the separate land regions in a grid map of land and water cells, where land cells connect only through shared edges. It tests systematic exploration of a two-dimensional grid, correct neighbor handling at borders and corners, and scaling to large grids where one region may cover everything.

  MicrosoftSoftware EngineerCoding & AlgorithmsOnsite
• Count words in a document robustlyMedium

  This question evaluates text-processing and algorithmic engineering skills, specifically precise tokenization rule definition, robust handling of Unicode and punctuation, streaming/large-file processing, unit testing for corner cases, and analysis of time and space complexity.

  MicrosoftSoftware EngineerData Manipulation (SQL/Python)Onsite
• Cross-Team Conflict Resolution & Product LaunchMedium

  Practice answering a PM behavioral prompt about cross-team leadership, engineering conflict, and customer-centric course correction. The model STARL response shows how to align multiple teams, resolve delivery trade-offs, respond to missed customer expectations, quantify impact, and explain learning.

  MicrosoftProduct ManagerBehavioral & LeadershipHR Screen
• Debug a Numerical Underflow in an A/B Testing Analytics Repo When the AI Agent Is WrongMedium

  An AI-assisted debugging exercise set in a multi-file A/B testing analytics codebase with five reported issues, centered on a numerical underflow that makes a sequential test stall on large experiments. It tests triage under a time limit, numerical root-cause analysis, and judging when an AI agent's proposed fix is wrong.

  MicrosoftSoftware EngineerSoftware Engineering FundamentalsOnsite
• Debug distributed-system performance problemsMedium

  This question evaluates a candidate's competency in diagnosing performance regressions in distributed systems and understanding of observability signals, latency and throughput trade-offs, and cross-component interactions within the Software Engineering Fundamentals domain.

  MicrosoftSoftware EngineerSoftware Engineering FundamentalsOnline Assessment
• Decode a JWT string without librariesHard

  This problem tests your understanding of the JSON Web Token (JWT) structure and your ability to manually implement Base64URL decoding and JSON deserialization in a constrained environment.

  MicrosoftSoftware EngineerCoding & AlgorithmsOnsite
• Deep-Clone a Hand-Built Doubly Linked List with an Arbitrary Special PointerMedium

  Implement your own doubly linked list whose nodes also carry a special pointer to any node in the list, then write a deep clone without using a built-in list type or adding fields to the node class. It tests pointer handling, mapping nodes by identity, edge cases such as null or self pointers, and proving the copy is fully independent.

  MicrosoftSoftware EngineerSoftware Engineering FundamentalsOnsite
• Describe Overcoming Challenges in Machine Learning ProjectsMedium

  This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Describe Overcoming Challenges in Machine Learning Projects states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  MicrosoftData ScientistBehavioral & LeadershipTechnical Screen
• Describe a recent innovation you deliveredMedium

  This question evaluates innovation, problem identification, stakeholder influence, trade-off management, measurable impact assessment, and reflective learning within the Behavioral & Leadership domain.

  MicrosoftSoftware EngineerBehavioral & LeadershipOnline Assessment
• Describe background and motivationsMedium

  This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Describe background and motivations states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  MicrosoftSoftware EngineerBehavioral & LeadershipTechnical Screen
• Describe handling ambiguity and resolving design conflictsMedium

  This question evaluates a software engineer's competencies in handling ambiguity, prioritization and delivery with limited guidance, risk management during migrations and experiments (including staged rollouts and A/B testing), and resolving technical design conflicts through stakeholder communication.

  MicrosoftSoftware EngineerBehavioral & LeadershipOnsite
• Describe leading an ambiguous ML project end-to-endMedium

  This Microsoft Data Scientist onsite behavioral question asks the candidate to narrate an end-to-end machine learning project they led under ambiguity, covering problem framing and success metrics tied to business KPIs, data sourcing and privacy constraints, model selection trade-offs across accuracy, latency, interpretability and cost, offline and online evaluation with a real experiment design, stakeholder alignment with PM, engineering and legal, staged rollout with rollback criteria, and post-launch monitoring. It also probes influence and judgment: a strong PM pushback resolved with data, a disagree-and-commit moment, one honest failure with its root cause, and how reproducibility, fairness and ethics held up under time pressure. Strong answers use STAR-L and quantify every claim, from PR-AUC and p95 latency to cost per thousand predictions and the confidence interval on the business lift.

  MicrosoftData ScientistBehavioral & LeadershipOnsite
• Describe motivation, ownership, and conflictMedium

  This question evaluates motivation, ownership, conflict-resolution, and leadership communication competencies, focusing on interpersonal dynamics and responsibility relevant to a Machine Learning Engineer role.

  MicrosoftMachine Learning EngineerBehavioral & LeadershipOnsite
• Describe resolving a conflict with a teammateEasy

  This Behavioral & Leadership interview question evaluates conflict resolution, interpersonal communication, ownership, and technical decision‑making skills within a data science and ML research project context.

  MicrosoftData ScientistBehavioral & LeadershipTechnical Screen
• Design A Low-Latency Product Price Update APIMedium

  Prepare for a read-heavy product pricing system design interview where prices update infrequently but launch-page reads must be low latency. The prompt focuses on versioned price records, caching, bulk reads, invalidation, rollback, and consistency after daily updates.

  MicrosoftSoftware EngineerSystem DesignOnsite
• Design A Scalable Web CrawlerMedium

  This question evaluates scalable system architecture and distributed systems competencies, specifically testing web crawler concepts such as URL discovery and deduplication, scheduling and prioritization, politeness-aware fetching, parsing and link extraction, storage of content and metadata, failure handling, and monitoring.

  MicrosoftSoftware EngineerSystem DesignTechnical Screen
• Design Anonymous Product Sharing with Every-Nth Visitor RewardsEasy

  Design product pages and trackable sharing links with anonymous-visitor limits, atomic every-Nth rewards, recoverable redemption, and engagement analytics.

  MicrosoftSoftware EngineerSystem DesignOnsite
• Design Chatbot Personalization MemoryMedium

  This problem evaluates the ability to design a scalable, low-latency memory system for an LLM-based chatbot that stores and retrieves user-specific facts to provide personalized responses.

  MicrosoftSoftware EngineerML System DesignOnsite
• Design Food-Delivery Proximity Search for Restaurants Within 10 kmMedium

  A system design exercise to build proximity search for a food-delivery app that finds restaurants within 10 km of a customer, followed by hand-coding the core lookup. It tests geospatial indexing, read and write paths, partitioning, handling dense areas, and turning a design into correct code.

  MicrosoftSoftware EngineerSystem DesignOnsite
• Design Product-Description Content Moderation at Marketplace ScaleMedium

  Design an ML moderation system for multilingual seller descriptions at marketplace scale. Cover policy-aware labels, severity-based actions, calibrated thresholds, human review and appeals, low-latency serving, selective rescans, auditability, drift, and adversarial abuse.

  MicrosoftData ScientistML System DesignTechnical Screen