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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
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- 11
- Topics
- 8
- Languages
Showing 5371–5400 of 9403 results
- MetaMediumSoftware EngineerSolve tree view and parentheses cleanup
This question evaluates binary tree traversal and view-extraction skills for the right-side view problem and string-processing and minimal-edit balancing for the parentheses cleanup, probing competency in data-structure traversal, state tracking, and correctness under edge cases.
Coding & AlgorithmsTechnical Screen - MetaEasyMachine Learning EngineerSolve two linked list/array tasks
This problem tests your ability to manipulate linked list pointers to detect cycles and solve a classic array-based problem using the two-pointer technique to find specific target sums.
Coding & AlgorithmsTechnical ScreenLinked ListTwo PointersArrays - MetaMediumSoftware EngineerSolve weighted pick and product except self
This question evaluates algorithm design and data-structure skills, focusing on weighted random selection and array aggregation for product computations within the Coding & Algorithms domain.
Coding & AlgorithmsOnline Assessment - MetaMediumSoftware EngineerSolve windowed duplicates and target expression
This question evaluates proficiency in windowed duplicate detection and time-space trade-offs for streaming or bounded-range scans, along with combinatorial expression generation and on-the-fly numeric evaluation using search, reflecting skills in algorithm design, data-structure selection, and numeric correctness.
Coding & AlgorithmsTechnical Screen - MetaMediumSoftware EngineerSolve word count, node, segmentation, stock tasks
This multipart question evaluates skills in tokenization and streaming text processing, generic rooted-tree data-structure design and traversal APIs, dictionary-based string segmentation (dynamic programming and prefix/prefix-structure optimization), and constrained algorithmic optimization for stock-trading problems.
Coding & AlgorithmsOnsite - MetaMediumSoftware EngineerSum Numbers Formed by Root-to-Leaf Paths
Tests traversal of a complete or sparse binary tree stored in an array, tracking path values to accumulate the total sum of numbers formed from root to leaf.
Coding & AlgorithmsOnsiteTreeDFSBinary Heap - MetaHardData ScientistTest if social users are more engaged
This problem tests your ability to design an analytical framework to measure user engagement, account for selection bias in non-randomized groups, and define robust metrics for comparing heterogeneous user populations.
Analytics & ExperimentationOnsiteAnalyticsCausal InferenceSelection Bias - MetaMediumData ScientistTest two models' proportions for significance
This question evaluates proficiency in statistical inference for proportions, covering hypothesis testing, confidence intervals, power and sample-size calculations, multiple-testing correction, and comparison of frequentist versus Bayesian approaches within the Statistics & Math domain for data scientist roles.
Statistics & MathOnsite - MetaMediumData ScientistTrack Metrics to Measure Push Notification Quality
Track Metrics to Measure Push Notification Quality evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Analytics & ExperimentationOnsite - MetaHardData ScientistTrack Success and Guardrail Metrics for Push Notifications
Evaluates success and guardrail metrics for a push-notification feature in a networked travel app. Strong answers measure incremental itinerary engagement and retention, monitor opt-outs and fatigue, and design a cluster or graph-aware experiment to reduce spillovers.
Analytics & ExperimentationTechnical Screen - MetaMediumSoftware EngineerTraverse binary tree by levels with constraints
This question evaluates binary tree traversal techniques, use of stacks as constrained data structures, predicate-based filtering of nodes, and the ability to argue algorithmic correctness and analyze time and space complexity.
Coding & AlgorithmsTechnical Screen - MetaMediumSoftware EngineerTraverse levels selecting nodes meeting a predicate
Traverse levels selecting nodes meeting a predicate 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 - MetaMediumSite Reliability EngineerTroubleshoot a production server outage
This question evaluates a candidate's competency in observability, incident response, and Linux/server operations, including troubleshooting production outages, isolating latency causes, identifying running processes and services, and recognizing finite resource bottlenecks.
Software Engineering FundamentalsTechnical Screen - MetaMediumSoftware EngineerTroubleshoot a single-node web outage
This question tests your ability to diagnose a sudden service outage on a single-node web server and your ability to propose architectural changes to prevent future single points of failure.
System DesignTechnical ScreenTroubleshootingAvailabilitySRE - MetaMediumSoftware EngineerTroubleshoot a website outage with disk full
This question tests your systematic approach to diagnosing a production service outage caused by resource exhaustion and your ability to implement short-term and long-term mitigation strategies.
Software Engineering FundamentalsTechnical ScreenLinuxSystem AdministrationIncident Response - MetaHardData ScientistUncover User Needs for Group Calling Effectively
Meta product analytics prompt on group calling, covering user-needs surveys, competitor benchmarking without direct data, experiment design, network effects, contamination, metrics, and guardrails.
Analytics & ExperimentationTechnical Screen - MetaMediumSoftware EngineerValidate Sorted Order Under a Custom Alphabet
This problem tests your ability to define custom comparison logic using a lookup table and verify if a list of strings adheres to a non-standard lexicographical ordering.
Coding & AlgorithmsTechnical ScreenArraysStringsSorting - MetaMediumSoftware EngineerValidate a simplified numeric string
This question evaluates string-parsing, formal-grammar validation, and edge-case reasoning competencies, including the ability to recognize valid numeric formats and to provide time and space complexity analysis.
Coding & AlgorithmsTechnical Screen - MetaMediumSite Reliability EngineerValidate abbreviations and brackets
This question evaluates proficiency in string parsing, pattern validation, and algorithmic correctness, covering abbreviation interpretation and bracket balancing while requiring careful handling of edge cases and input constraints.
Coding & AlgorithmsTechnical Screen - MetaMediumData EngineerValidate alternating checkout/return logs
This question evaluates the ability to process sequential event logs, maintain per-entity state invariants (checkout vs return), and reason about algorithmic time and space complexity within a validation task.
Coding & AlgorithmsTechnical Screen - MetaMediumData EngineerValidate carpool capacity
This question evaluates understanding of interval-based resource accounting and algorithmic reasoning with cumulative constraints, assessing skills in processing time-bound events and managing capacity limits.
Coding & AlgorithmsOnsite - MetaMediumSoftware EngineerValidate parentheses and find k-th largest
This problem tests your ability to handle nested structures using a stack and your efficiency in order-based selection using heap operations.
Coding & AlgorithmsTechnical ScreenStackHeapQuickSelect - MetaMediumSoftware EngineerValidate word abbreviation and reconcile two abbreviations
Validate word abbreviation and reconcile two abbreviations 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 & AlgorithmsOnsite - MetaMediumData EngineerVisualize Netflix metric trends
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 Visualize Netflix metric trends states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Analytics & ExperimentationOnsite - MetaHardSoftware EngineerWalk through a resume deep dive
This question evaluates ownership, technical leadership, system design, and operational reliability by requiring an end-to-end deep dive into an infrastructure project covering problem definition, architecture, scaling (QPS, latency, storage), SLOs, incident response, and impact metrics.
Behavioral & LeadershipOnsite - MetaMediumSoftware EngineerWalk through resume and plan team success
This question evaluates leadership, impact-focused communication, problem-solving, prioritization, and cross-functional collaboration skills via an end-to-end resume walkthrough and a 90-day team success plan, and it sits in the Behavioral & Leadership category; the level of abstraction is practical application, emphasizing demonstrated impact and near-term execution. It is commonly asked in technical interviews to reveal a candidate's ability to articulate measurable accomplishments, explain difficult technical or organizational challenges, and present structured, outcome-oriented plans and metrics that indicate interpersonal influence and operational readiness.
Behavioral & LeadershipTechnical Screen - MetaMediumData ScientistWhat features and feature selection would you use?
This question evaluates feature engineering, feature selection, and production-aware machine learning system design skills for ranking shop ads, within the Machine Learning domain for a Data Scientist role.
Machine LearningTechnical Screen - MetaMediumData ScientistWhich clustering algorithm would you use and why
A Meta Data Scientist machine learning screen on choosing a clustering algorithm for social-product users. It contrasts traditional feature-vector clustering (k-means, GMM, hierarchical, DBSCAN/HDBSCAN) with social-graph community detection (Louvain/Leiden, spectral, SBM, node embeddings), and covers preprocessing, choosing the number of clusters, evaluation, directed/weighted graphs, and scaling to millions of users.
Machine LearningTechnical Screen - MetaMediumData ScientistWrite SQL filtering, grouping, CASE, UNION tasks
This question evaluates proficiency with SQL filtering, aggregation, conditional logic, and set operations—specifically skills around WHERE filtering, GROUP BY/HAVING, CASE bucketing, FLOOR on aggregates, and UNION versus UNION ALL—within the Data Manipulation (SQL/Python) domain and emphasizes practical application of ANSI SQL.
Data Manipulation (SQL/Python)HR Screen - MetaMediumData ScientistWrite SQL for CTR and Revenue
This question tests the ability to join event logs with reference data, perform conditional aggregation to calculate click-through rates (CTR), and apply date-sensitive currency conversions.
Data Manipulation (SQL/Python)Technical ScreenSQLData AggregationJoin
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