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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 5251–5280 of 9403 results
- MetaMediumData EngineerMeasure Game Monetization and Validate a Reporting Repair
Define gaming monetization metrics, separate business changes from data failures, and validate repairs with reconciliation and guardrails.
Analytics & ExperimentationTechnical Screen - MetaMediumData ScientistMeasure Harmful Content Impact with Key Metrics
This interview question evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer for Measure Harmful Content Impact with Key Metrics states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Analytics & ExperimentationTechnical Screen - MetaMediumData ScientistMeasure a friend-recommendation launch
This question evaluates experiment design, metric selection, causal inference and business-metric translation for social features, including defining primary and guardrail metrics, choosing experimental units to mitigate network interference, and estimating revenue impact from observed lifts.
Analytics & ExperimentationOnsite - MetaMediumData ScientistMeasure and mitigate notification spam
This question tests the ability to design an experimentation framework for notification systems while accounting for user fatigue, long-term ecosystem health, and signal interference.
Analytics & ExperimentationTechnical ScreenExperimentationProduct MetricsCausal Inference - MetaHardData ScientistMeasure impact of bot mitigation via experiment
This question evaluates experiment design and causal inference skills for platform analytics, covering interference management, metric and guardrail definition, power and duration calculations, eligibility and exclusions, novelty/adaptation considerations, and diagnostics for bot‑mitigation interventions.
Analytics & ExperimentationOnsite - MetaMediumData ScientistMeasure scheduled posts feature success
This question evaluates proficiency in Bayesian statistical estimation, experimental design, product metric definition, and causal/confounder analysis for measuring feature reliability and engagement.
Analytics & ExperimentationOnsite - MetaMediumSoftware EngineerMerge Two Lists of Non-Overlapping Intervals
This question evaluates a candidate's ability to merge two pre-sorted, non-overlapping interval lists into a single consolidated set, a core array and two-pointer/merging skill in coding interviews. It tests correct handling of edge cases like touching endpoints versus true gaps, assessing precision in interval logic and algorithmic reasoning under linear-time constraints.
Coding & AlgorithmsOnsite - MetaHardSoftware EngineerMerge customers and preserve history
A Meta software-engineer system-design take-home: implement mergeCustomers(oldId, newId) for a payments/ledger platform, absorbing one customer into another while preserving every account's balance and immutable transaction history. Tests identity unification, ownership remap, conflict/duplicate resolution, top-N leaderboard maintenance, atomicity, concurrency, idempotency, and complexity analysis.
System DesignOnline Assessment - MetaMediumSoftware EngineerMerge overlapping intervals
This problem tests your ability to manipulate array-based data by sorting and performing linear sweeps to consolidate overlapping ranges.
Coding & AlgorithmsOnsiteArraysSortingGreedy - MetaMediumSoftware EngineerMerge two interval lists into a union
This question evaluates a candidate's ability to implement interval merging algorithms, reason about edge cases such as touching boundaries, empty inputs, and invalid intervals, and perform time and space complexity analysis.
Coding & AlgorithmsTechnical Screen - MetaHardProduct ManagerMeta PM Interview Questions
Practice a mixed PM onsite loop with strategy, data, product design, architecture, analytics, technical leadership, and failure reflection prompts. The solution guide shows how to structure each case, ask clarifying questions, choose metrics, make trade-offs, and give practical recommendations.
Product / Decision MakingOnsite - MetaMediumProduct ManagerMeta Pay: Metrics & Prioritization
Practice Meta Pay PM metrics and prioritization with North Star definition, metric tree, split-bill versus donations trade-offs, and debugging flat adoption despite lower cost per transaction. The solution covers active payers, transaction success, trust, risk, unit economics, feature strategy, and decomposition analysis.
Product / Decision MakingOnsite - MetaMediumSoftware EngineerMinimum Round-Trip Flight Cost
This question evaluates a candidate's ability to optimize over paired sequences using array traversal and running-minimum tracking, a core array-processing technique in coding interviews. It tests practical application of single-pass optimization under an ordering constraint rather than brute-force pairwise comparison, commonly used to assess algorithmic efficiency and edge-case handling.
Coding & AlgorithmsOnsite - MetaMediumData ScientistModel Unique Recipients with Poisson Distribution and Test Fit
Evaluates statistical modeling of unique recipient counts per caller using count distributions. Strong answers compare Poisson, binomial, negative binomial, zero-inflated, and segmented models, then test fit with dispersion checks, likelihood metrics, chi-square tests, and simulation-based diagnostics.
Statistics & MathTechnical Screen - MetaMediumData ScientistModel session times and comments with exponential/Poisson
This question evaluates understanding of memoryless processes and count-data modeling, covering exponential (constant-hazard) distributions for session durations and Poisson approximations for comment counts within survival analysis and count-data modeling in Statistics & Math for a Data Scientist role.
Statistics & MathOnsite - MetaMediumSoftware EngineerMove Work Forward Across Teams
This question evaluates your ability as a senior engineer to drive cross-functional alignment, manage complex technical dependencies, and deliver impact across multiple teams with competing priorities.
Behavioral & LeadershipOnsiteBehavioralCross-Team CollaborationLeadership - MetaHardSoftware EngineerNavigate Stakeholder Conflict During a Compressed Delivery Timeline
Describe a project where a deadline moved earlier and stakeholders disagreed about what should ship. Explain how you exposed the conflict, tested a failing approach, incorporated senior feedback, changed course, and used a concrete result to assess the compromise.
Behavioral & LeadershipOnsite - MetaMediumSoftware EngineerNavigate unknown grid to locate target
This question evaluates algorithmic problem-solving and spatial reasoning skills, particularly graph traversal, exploration in unknown environments, state encoding for relative coordinates, and reasoning about correctness.
Coding & AlgorithmsTechnical Screen - MetaMediumProduct ManagerNorth-star and guardrail metrics for generative AI across Meta's apps
A product manager metrics question on judging whether Meta's generative AI features, such as its in-app assistant, creation tools and ad tools, are succeeding. It tests choosing a north-star metric that reflects real value, supporting and guardrail metrics, and how to show the AI actually caused any change.
Analytics & ExperimentationOther - MetaMediumData ScientistOptimize Oculus Data Streaming with Bandwidth Constraints
This question evaluates a candidate's ability in algorithm design and problem decomposition for array segmentation and interval coverage, focusing on reasoning about cumulative constraints for streaming data and geometric interval intersections.
Coding & AlgorithmsOnsite - MetaMediumData ScientistOptimize Travel Costs and Generate Rotational Symmetric Numbers
This question evaluates algorithmic optimization and complexity-analysis skills by combining array-based time-dependent pricing for round-trip cost minimization with combinatorial generation of rotationally symmetric (strobogrammatic) k-digit numbers.
Coding & AlgorithmsTechnical Screen - MetaHardMachine Learning EngineerOptimize a Fifteen-Sum Card Strategy
This problem tests your ability to optimize a combinatorial search space through memoization and dynamic programming to determine the maximum win rate of a card-based strategy.
Coding & AlgorithmsOnsiteCombinatoricsProbabilityRecursion - MetaMediumSoftware EngineerOptimize flight costs and find grid path
This question evaluates algorithm design and problem-solving skills for array-based cost optimization and grid pathfinding, including selection under ordering constraints, path existence detection and path reconstruction, together with correctness and edge-case reasoning.
Coding & AlgorithmsTechnical Screen - MetaMediumMachine Learning EngineerOptimize repeated-value vectors and compute exclusive times
This question evaluates proficiency in data-structure and algorithmic concepts such as run-length encoding for compressed vectors and interval/nesting reasoning for computing exclusive execution times.
Coding & AlgorithmsTechnical Screen - MetaMediumMachine Learning EngineerOptimize ribbon piece length by binary search
This question evaluates understanding of binary-search-on-answer techniques and monotonic predicates, complexity analysis, and implementation-level handling of integer overflow and extreme edge cases in numeric partitioning, situated in the coding and algorithms domain and emphasizing practical implementation considerations rather than purely theoretical proofs. It is commonly asked because it reveals whether an interviewee can reason about monotonicity and design an O(n log max(lengths)) solution that remains robust under very large k, large element values, and potential integer overflow.
Coding & AlgorithmsOnsite - MetaMediumSoftware EngineerPalindrome After Deleting at Most One Character
This problem tests your ability to optimize string traversal using a two-pointer approach, specifically handling conditional branch logic when an inconsistency is detected.
Coding & AlgorithmsTechnical ScreenStringsTwo PointersGreedy - MetaHardData ScientistPersuade engineers to launch pinned-unread chats
This question evaluates persuasion, product sense, metrics-driven reasoning, and technical trade-off analysis for a Data Scientist within a Behavioral & Leadership domain, requiring clear problem definition, baseline metrics, impact estimation, and consideration of engineering constraints like ranking complexity, real-time updates, caching, client performance, edge cases, and accessibility. It is commonly asked to assess the ability to influence engineering stakeholders, design incremental rollouts with success metrics and guardrails, and balance high-level conceptual strategy with practical implementation planning (both conceptual understanding and practical application).
Behavioral & LeadershipTechnical Screen - MetaMediumSoftware EngineerPrepare answers for core behavioral questions
This question set evaluates interpersonal and leadership competencies such as communication, conflict resolution, giving and receiving feedback, problem-solving, ownership, handling ambiguity, and the ability to articulate measurable impact and self-awareness.
Behavioral & LeadershipOnsite - MetaMediumMachine Learning EngineerPrevent Private Code Leakage in Coding Agents
This problem tests the ability to design an ML-driven safeguard system that prevents private codebase exposure during the training, fine-tuning, and inference phases of a coding agent.
ML System DesignTechnical ScreenMLOpsSecurityPrivacy - MetaMediumSoftware EngineerProduce asymmetric side views of a binary tree
Produce asymmetric side views of a binary tree 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
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