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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
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- 8
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Showing 3121–3150 of 3640 results
- SnapchatHardSoftware EngineerCompute shortest path in a 2D grid
This question evaluates understanding of graph traversal and pathfinding concepts, including modeling a 2D grid as a graph and reasoning about shortest-path computations and obstacle handling.
Coding & AlgorithmsOnsite - SnapchatMediumSoftware EngineerCount Grid Islands That Never Touch the Border
Coding problem on a binary grid where 0 marks land and 1 marks water: count the islands, connected horizontally or vertically, that have no cell on the grid's border. It tests grid traversal, connected components and careful handling of islands that reach the edge through a single cell.
Coding & AlgorithmsOnsite - SnapchatHardSoftware EngineerCount ways to decode digit string
This question evaluates a candidate's skill in dynamic programming and combinatorial reasoning about string partitioning, testing competency in counting valid decodings under constraint handling and edge-case analysis.
Coding & AlgorithmsOnsite - SnapchatMediumData ScientistDesign A/B Tests for Banner Ad and Group-Story Feature
Evaluates A/B test design for a banner ad and a group-story feature in a social app. Strong answers define monetization, engagement, safety, and retention metrics, handle accidental clicks for ads, account for network effects in group stories, and set launch criteria with guardrails.
Analytics & ExperimentationOnsite - SnapchatMediumSoftware EngineerDesign a Column-Queryable KV Database
This problem tests your ability to design a distributed key-value storage system that supports efficient column-based filtering and range scans, balancing write performance against analytical query capabilities.
System DesignOnsiteDistributed SystemsNoSQLStorage - SnapchatMediumSoftware EngineerDesign a Metrics System
Design a high-throughput, low-latency metrics collection, aggregation, and querying platform. The question tests your ability to handle multi-dimensional time-series data, mitigate high-cardinality label explosions, and design tiered storage for varying query windows.
System DesignOnsiteTime SeriesDistributed SystemsScalability - SnapchatHardSoftware EngineerDesign a News Aggregator
This question evaluates a candidate's ability to design scalable content ingestion and distribution systems, encompassing API-driven fetching, scheduling, deduplication, storage, ranking, freshness guarantees, API rate limiting, and efficient article serving.
System DesignOnsite - SnapchatMediumSoftware EngineerDesign a Pre-Login Risk and Challenge Service
Design a low-latency, resilient pre-login security service that evaluates risk signals, issues dynamic verification challenges, and verifies responses without exposing authentication flows to replay attacks.
System DesignOnsiteSecurityDistributed SystemsAuthentication - SnapchatMediumMachine Learning EngineerDesign a Product Tagging Pipeline
This problem tests your ability to design a scalable multi-modal machine learning pipeline that processes diverse content types to generate standardized taxonomy tags for an e-commerce platform.
ML System DesignOnsiteComputer VisionNLPMulti-modal - SnapchatMediumMachine Learning EngineerDesign a Trustworthy Ranking System
This problem tests the ability to design an end-to-end ML system for ranking content while balancing engagement metrics with safety, misinformation, and user trust.
ML System DesignOnsiteRankingTrust & SafetyMulti-objective Optimization - SnapchatMediumSoftware EngineerDesign a device owner lookup service
This question tests the ability to design a distributed system for tracking the mapping between ephemeral devices and their currently signed-in users, focusing on handling event concurrency and high-throughput read/write operations.
System DesignOnsiteDistributed SystemsConcurrencyCaching - SnapchatHardMachine Learning EngineerDesign a harmful content detection system
This question evaluates proficiency in ML system design for harmful-content detection, assessing competencies in multimodal modeling, taxonomy and labeling strategies, data strategy, privacy-aware architecture, real-time inference, human-in-the-loop decisioning, and operational reliability for global consumer platforms.
ML System DesignOnsite - SnapchatMediumSoftware EngineerDesign a metrics collection and alerting system
This question evaluates system design competencies such as scalable time-series data modeling, ingestion and storage architecture, query latency versus retention trade-offs, and alert evaluation logic within the System Design domain.
System DesignOnsite - SnapchatMediumMachine Learning EngineerDesign a search-to-ads ranking pipeline
This question tests the ability to design a high-throughput, low-latency ranking system that balances user experience with monetization goals through multi-stage retrieval and bidding mechanics.
System DesignOnsiteRankingRecommendation-SystemsAd-Tech - SnapchatHardSoftware EngineerDesign a streaming ads system
This question evaluates a candidate's competency in designing low-latency, scalable, and privacy-compliant ad-insertion platforms, encompassing distributed systems, real-time bidding integration, ad format and measurement standards, content and identity signal processing, pacing/frequency control, and multi-region fault tolerance.
System DesignOnsite - SnapchatMediumSoftware EngineerDesign a swipeable video feed backend
This question evaluates system-design competence for building scalable, low-latency backend services that handle feed vending, pagination, personalized ranking, caching, storage, and content eligibility; it is categorized under System Design and tests practical application of distributed systems and backend data engineering principles.
System DesignOnsite - SnapchatHardMachine Learning EngineerDesign an Advertising or Recommendation Model End to End
Design a recommendation model from labels and sampling through features, loss, ranking metrics, online experiments, and production debugging.
ML System DesignOnsite - SnapchatMediumMachine Learning EngineerDesign an ads ranking ML system
This question tests the ability to design an end-to-end ads ranking pipeline, focusing on latency constraints, mitigation of position bias, and balancing multi-objective optimization.
ML System DesignOnsiteAds RankingMulti-Task LearningSystem Design - SnapchatHardSoftware EngineerDesign product co-occurrence analytics API
This question evaluates design skills for RESTful APIs and backend systems, covering API schema and versioning, authentication and rate limiting, caching and cache invalidation, storage models, precomputation pipelines, consistency and staleness bounds, monitoring, and operational concerns.
System DesignOnsite - SnapchatMediumSoftware EngineerDesign real-time ad impression and spend tracking
This question tests the ability to design a high-throughput, fault-tolerant system capable of tracking massive volumes of ad impression events and calculating real-time budget spending.
System DesignOnsiteDistributed SystemsCachingHigh Throughput - SnapchatHardMachine Learning EngineerDesign real-time top-K POI retrieval on maps
This question evaluates a candidate's ability to design scalable, low-latency real-time retrieval and personalized ranking systems for geospatial data, testing competencies in spatial indexing and tiling, candidate generation versus re-ranking pipelines, caching and freshness strategies, latency and availability SLOs, deduplication and pagination, and model/ANN decision-making; the domain is ML system design for map-based POI retrieval and it assesses both high-level architectural reasoning and practical engineering trade-offs. Such problems are commonly asked to assess how an engineer balances consistency, stability and freshness under strict latency and availability targets while reasoning about operational concerns like load shedding, offline versus online evaluation, instrumentation and cost.
ML System DesignOnsite - SnapchatHardSoftware EngineerDesign ride-hailing and price alert systems
This question evaluates a candidate's competency in large-scale system design, including distributed architecture, real-time data processing, geo-spatial indexing and low-latency matching for ride-hailing, plus scalable ingestion, time-series storage, rule evaluation, and reliable notification pipelines for price-tracking, within the System Design domain. It is commonly asked to assess architectural trade-offs around scalability, consistency, availability, fault tolerance and operational concerns, testing practical application of architectural patterns alongside conceptual understanding of data modeling and real-time constraints.
System DesignOnsite - SnapchatMediumMachine Learning EngineerDetermine and print expression to reach target
This question evaluates skill in constructing and evaluating arithmetic expressions, handling numerical stability (including division-by-zero and floating-point tolerance), and reasoning about combinatorial permutations of numbers and operators.
Coding & AlgorithmsOnsite - SnapchatMediumSoftware EngineerDetermine blockage and parse HTML tokens
This question evaluates computational geometry and graph connectivity for the circular-stones subproblem and parsing plus tree data-structure manipulation for the HTML-like token subproblem, measuring skills in modeling spatial overlap, graph traversal/union operations, hierarchical DOM construction, and dynamic node insertion/deletion.
Coding & AlgorithmsOnsite - SnapchatMediumSoftware EngineerEngineering Manager Behavioral: Motivation, Taking Feedback and Leading a Reorganization
A Snapchat engineering manager behavioral question in three parts: what motivates you in this role, how you take critical feedback, and how you led a team through a restructuring. It tests self-awareness, growth from feedback, transparent communication and care for people during change.
Behavioral & LeadershipOnsite - SnapchatMediumSoftware EngineerEngineering Manager Scenarios: Promotion Cases, Team Conflict and Performance Plans
A Snapchat engineering manager leadership question covering three people-management scenarios: building a case to promote an engineer, resolving conflict on your team, and managing underperformance through a performance improvement plan. It tests fairness, judgment and coaching.
Behavioral & LeadershipOnsite - SnapchatMediumMachine Learning EngineerExplain BatchNorm, optimizers, and L1/L2
This question tests your conceptual understanding of how normalization, optimization strategies, and regularization techniques influence training stability, convergence, and model sparsity.
Machine LearningOnsiteDeep LearningOptimizationRegularization - SnapchatMediumMachine Learning EngineerExplain Core ML Concepts
This question tests the ability to explain foundational machine learning trade-offs and architectural nuances in deep neural networks.
Machine LearningOnsiteDeep LearningOptimizationStatistics - SnapchatHardMachine Learning EngineerExplain Neural-Network Regularization and Dropout
Explain L1, L2, dropout scaling, train/inference behavior, early stopping, and the difference between gradient penalties and decoupled weight decay.
Machine LearningOnsite - SnapchatMediumMachine Learning EngineerFind K Nearest Points
This question tests the ability to efficiently find the k-closest points to an origin in a 2D plane, focusing on heap-based or selection-based data structures.
Coding & AlgorithmsOnsiteHeapGeometryQuickSelect
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