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Interview Questions
Practice 9403 coding, system design and machine learning questions from 546 companies, sorted by role, topic and interview round. Every question has step-by-step hints, a code runner that supports 8 languages and an AI mentor; members also get the full solution walkthrough.
- 9403
- Questions
- 546
- Companies
- 11
- Topics
- 8
- Languages
Showing 5311–5340 of 9403 results
- MetaHardSoftware EngineerReturn the Minimum-Sum Root-to-Leaf Path
Tests tree traversal, path reconstruction, tie-breaking logic, and handling deeply skewed trees with up to 100,000 nodes without exceeding recursion depth limits.
Coding & AlgorithmsOnsitebinary-treedfsstack - MetaMediumData EngineerReturn top-3 content per category
This question evaluates the ability to perform grouped top-k selection, deterministic tie-breaking and ordering, and to reason about algorithmic efficiency when manipulating structured datasets in the Data Manipulation (SQL/Python) domain for a Data Engineer role.
Data Manipulation (SQL/Python)Onsite - MetaMediumSoftware EngineerReverse between equal-value nodes in list
This question evaluates a candidate's ability to manipulate singly linked lists, perform in-place sublist reversal, and manage pointer references and node boundaries.
Coding & AlgorithmsTechnical Screen - MetaMediumSoftware EngineerReverse sublist between equal-value nodes
This question evaluates linked-list manipulation and pointer-management skills, focusing on reversing an in-place sublist between two nodes with equal values while respecting O(n) time and O(1) extra space constraints.
Coding & AlgorithmsTechnical Screen - MetaMediumProduct ManagerRoot-Causing an Instagram Satisfaction Decline During Ad Monetization Growth
A Meta product manager interview question about Instagram, where ad revenue has risen while user satisfaction has fallen. It tests validating both metrics, decomposing revenue and satisfaction to find a shared cause, testing hypotheses with holdouts, and weighing short-term revenue against long-term user health.
Analytics & ExperimentationOther - MetaMediumData ScientistRun a clean A/B test for recommendations
This question evaluates a data scientist's competency in experimental design, causal inference, and statistical power analysis for A/B tests, covering randomization unit choice, contamination prevention, metric and guardrail selection, clustering adjustments, and bias-control techniques.
Analytics & ExperimentationOnsite - MetaMediumSoftware EngineerScale a Cache or Rate Limiter Across Multiple Machines
Tests your ability to design a horizontally scalable distributed rate limiter and caching layer, focusing on data partitioning, hot-key mitigation, failure modes, and consistency trade-offs.
System DesignOnsitesystem-designdistributed-systemsrate-limiting - MetaMediumData ScientistSelect and prioritize metrics with guardrails
This question evaluates a candidate's ability to design a robust metrics framework for product experiments, covering selection and normalization of success metrics, feature-only sizing and ecosystem metrics, explicit cannibalization reads, guardrails, multiple-testing control, and back-of-the-envelope LTV/ARPDAU impact estimation.
Analytics & ExperimentationTechnical Screen - MetaMediumSoftware EngineerSelect words to maximize unique characters
This question evaluates understanding of combinatorial search and string manipulation, specifically the ability to reason about unique-character constraints, subset selection, and set-like representations.
Coding & AlgorithmsOnsite - MetaHardMachine Learning EngineerSelf-Attention: Implementation, Complexity, and Efficient Variants
Tests a candidate's mathematical and practical grasp of scaled dot-product attention, its computational and memory bottlenecks, and modern algorithmic optimizations like FlashAttention and linear attention.
Machine LearningOnsitetransformerattention-mechanismflashattention - MetaMediumSoftware EngineerSet up a Python interview environment
This question evaluates proficiency in Python development environment setup, including dependency and virtual environment management, secure handling of environment variables for secrets, tooling for rapid feedback, reproducibility practices, and basic service scaffolding.
Data Manipulation (SQL/Python)Onsite - MetaMediumSoftware EngineerShare different perspective from leadership feedback
This question evaluates a software engineer's ability to receive and integrate leadership feedback, measuring competencies such as adaptability, self-awareness, communication, and accountability.
Behavioral & LeadershipOnsite - MetaHardData ScientistShould We Launch Group Calling?
A Meta Data Scientist technical-screen case: using only one-to-one call logs, decide whether to build a group calling feature and how to measure a launch's success. It tests product analytics, proxy-metric design, network analysis, causal inference, and experiment design under social-network interference.
Analytics & ExperimentationTechnical Screen - MetaHardMachine Learning EngineerSimulate Monster Team Battles
This question tests the ability to implement a stateful, turn-based simulation engine using object-oriented principles, efficient queue management, and rule-based damage calculations.
Coding & AlgorithmsTechnical ScreenSimulationObject-Oriented DesignSorting - MetaMediumData ScientistSize opportunity for new product line
This question evaluates a data scientist's skills in financial opportunity sizing, sensitivity analysis, and experimental design by requiring quantitative modeling of impacted users, incremental orders, revenue, and gross profit for a proposed product line.
Analytics & ExperimentationOnsite - MetaMediumSoftware EngineerSolve Array, Matrix, and Recommendation Problems
This question evaluates algorithmic skills across array manipulation, grid pathfinding, and graph-based recommendation systems, testing competencies in in-place transformations, efficient traversal/search, and candidate ranking under constraints.
Coding & AlgorithmsOnsite - MetaMediumSoftware EngineerSolve Four Online Assessment Problems
This multi-part question evaluates algorithmic problem-solving across array manipulation, exact fraction comparison, scheduling and simulation with ordered event lists, matrix transformation operations, and string concatenation/counting, exercising skills in data structures, searching, and combinatorial counting.
Coding & AlgorithmsTechnical Screen - MetaMediumSoftware EngineerSolve Matrix, Tree, Nested, LCA, Maze Tasks
This set of tasks evaluates algorithm design and data structure competencies across matrix traversal, tree path-sum aggregation, nested-list depth weighting, lowest common ancestor discovery using parent pointers, and several rolling-maze reachability and shortest-path variants.
Coding & AlgorithmsOnsite - MetaMediumSoftware EngineerSolve Maze and Suffix Problems
This two-part question evaluates stateful graph traversal and shortest-path reasoning under key-and-door constraints, alongside efficient string-suffix matching and scalable data-structure design, testing competencies in state management, graph/search algorithms, string algorithms, and algorithmic optimization.
Coding & AlgorithmsOnsite - MetaMediumSoftware EngineerSolve PTO window and sparse unique counting
Solve PTO window and sparse unique counting 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.
Coding & AlgorithmsTechnical Screen - MetaMediumSoftware EngineerSolve Parser, Trading, Tree, And Deck Tasks
This question evaluates input validation and parsing for numeric literals, array-based algorithmic optimization for single-trade profit, tree traversal for extracting rightmost nodes per depth, and software design for a stateful card-deck with shuffle and testing.
Coding & AlgorithmsOnsite - MetaMediumData EngineerSolve Python and SQL data tasks
This question evaluates data manipulation and engineering competencies by testing Python proficiency with nested data structure handling, complexity analysis and test-case design, alongside SQL proficiency in UTC-aware aggregation and per-user deduplication to compute daily active users; it is categorized as Data Manipulation (SQL/Python) within the data engineering domain. Such problems are commonly asked to assess practical implementation ability and robustness under edge cases, as well as conceptual understanding of time/space complexity and correct date-time handling, reflecting a primarily practical application with elements of conceptual analysis.
Data Manipulation (SQL/Python)Technical Screen - MetaMediumData EngineerSolve SQL and Python coding tasks
This question evaluates SQL proficiency in relational querying (joins, filtering, aggregation) and Python algorithmic problem-solving for non-adjacent selection, measuring a data engineer's ability to manipulate relational data and implement efficient algorithms.
Coding & AlgorithmsTechnical Screen - MetaMediumSoftware EngineerSolve Three Coding Interview Problems
This set of tasks evaluates proficiency in data structures and algorithms, covering tree traversal and lowest common ancestor reasoning, interval merging and overlap resolution, and combinatorial subset selection under uniqueness constraints.
Coding & AlgorithmsTechnical Screen - MetaMediumSoftware EngineerSolve Tree Diameter and Palindromic Counts
This problem tests your ability to perform recursive depth-first searches on binary trees and efficient string manipulation to count palindromic subsequences or paths.
Coding & AlgorithmsOnsiteTreesDFSString - MetaEasySoftware EngineerSolve Tree View and Triplet Sum
This multipart question evaluates proficiency with tree-based data structures and array-based algorithmic problem solving, focusing on reasoning about which nodes are visible from a binary tree's right side and identifying unique zero-sum triplets in an integer array; it tests concepts such as tree traversal, duplicate handling, and algorithmic complexity analysis. These problems are commonly asked to assess algorithmic problem-solving ability, manipulation of fundamental data structures, and attention to edge cases and performance, and they fall under the Coding & Algorithms category with a focus on practical application of algorithmic concepts supported by conceptual understanding of data structures and complexity.
Coding & AlgorithmsTechnical Screen - MetaEasyMachine Learning EngineerSolve Tree Views, Columns, and Calculator
This problem tests your ability to perform recursive binary tree traversals to extract horizontal and vertical views, followed by implementing a stack-based parser to handle mathematical expressions with standard order of operations.
Coding & AlgorithmsOnsiteBinary TreesBFSStack - MetaHardSoftware EngineerSolve Two Backtracking Array Problems
This prompt evaluates algorithmic problem-solving skills focused on combinatorial search and backtracking, including handling duplicate values, index distinctness, and enforcing character-uniqueness constraints across concatenated subsets.
Coding & AlgorithmsTechnical Screen - MetaMediumSoftware EngineerSolve UTF-8 Validation & Shortest Path
This pair of problems evaluates skills in data encoding interpretation and graph traversal, examining competency in validating byte-oriented input formats and computing shortest paths on binary matrices.
Coding & AlgorithmsTechnical Screen - MetaMediumSoftware EngineerSolve a Key-Door Corridor Maze
This problem tests your ability to model a search space beyond simple coordinate traversal by incorporating state-dependent constraints (keys) using Breadth-First Search.
Coding & AlgorithmsOnsiteBFSBitmaskShortest Path
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