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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.
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- 11
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Showing 7771–7800 of 9403 results
- SnapchatMediumSoftware EngineerCheck if a binary tree is complete
This problem tests your understanding of binary tree properties and your ability to perform a level-order traversal to verify structural completeness.
Coding & AlgorithmsTechnical ScreenBinary TreeBFSData Structures - SnapchatHardMachine Learning EngineerCompare Batch Normalization and Layer Normalization
Compare batch and layer normalization by their axes, learned parameters, running statistics, batch-size effects, and training-to-inference debugging.
Machine LearningOnsite - SnapchatHardSoftware EngineerCompare WebSocket, SSE, and long polling
This question tests a software engineer's depth in web networking fundamentals, covering real-time communication protocols and the OSI and TCP/IP models. It assesses practical knowledge of WebSocket, SSE, and long polling trade-offs, as well as understanding of how modern transport protocols like QUIC differ from TCP in multiplexing, handshake latency, and connection migration.
Software Engineering FundamentalsOnsite - SnapchatMediumMachine Learning EngineerCompare convolutions and transformers
This question evaluates understanding of neural network architectures, focusing on inductive biases, data and compute trade-offs, mechanisms for handling long-range dependencies, domain-specific roles in vision and NLP, and modern hybrid approaches that address architecture limitations.
Machine LearningTechnical Screen - SnapchatMediumData ScientistCompute CTR and metrics with pandas
This question evaluates proficiency in time-series and event-level data manipulation with pandas, including CTR computation, event denoising and deduplication, sessionization, cohort analysis, temporal joins, and performance-aware vectorized operations within the Data Manipulation (SQL/Python) domain.
Data Manipulation (SQL/Python)Onsite - SnapchatMediumData ScientistCompute User Retention and Analyze Event Data
This question evaluates a candidate's ability to perform SQL and Python data manipulation for event analytics, including cohort retention, aggregation of distinct purchasing users, median-of-daily-events calculations, and hourly time-series grouping.
Data Manipulation (SQL/Python)Onsite - SnapchatMediumSoftware EngineerCompute islands in a binary grid
This question evaluates a candidate's competency in modeling grids as graphs, detecting connected components, applying graph traversal algorithms (DFS/BFS) and disjoint-set (Union-Find) data structures, and analyzing algorithmic time and space complexity.
Coding & AlgorithmsOnsite - SnapchatHardSoftware EngineerCompute longest increasing path in matrix
This question evaluates algorithmic problem-solving skills in graph traversal and dynamic programming on matrices, measuring understanding of state representation and performance trade-offs in grid-based searches within the Coding & Algorithms domain.
Coding & AlgorithmsOnsite - SnapchatMediumData ScientistCompute same-day acceptance metrics last week
This question evaluates proficiency in time-based data manipulation, SQL JOINs and aggregations, handling NULLs and missing reference rows, and computing acceptance and percentage metrics with careful UTC date boundary treatment.
Data Manipulation (SQL/Python)Technical Screen - 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 EngineerCompute shortest recursive string encoding
This question evaluates proficiency in string manipulation, pattern detection, recursion, and dynamic programming for efficient sequence compression in the Coding & Algorithms domain.
Coding & AlgorithmsOnline Assessment - SnapchatMediumSoftware EngineerCompute sliding window median
This question evaluates the ability to maintain a running median over a sliding window, testing competencies in data structures, order statistics, dynamic updates, and algorithmic efficiency within the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen - 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 - SnapchatMediumData ScientistCount Users Whose First Daily Event Is App Launch
Write a PostgreSQL query to identify each user's first event per calendar day and aggregate the distinct user count by operating system and device when that first event is an app launch. Tests window functions, tie-breaking logic, and multi-dimensional grouping.
Data Manipulation (SQL/Python)Technical ScreenSQLPostgreSQLWindow Functions - SnapchatMediumSoftware EngineerCount islands with eight-direction adjacency
This question evaluates a candidate's competency in graph traversal algorithms and data-structure trade-offs by counting connected components on a grid with eight-direction adjacency, focusing on BFS/DFS behavior and optional Union-Find approaches.
Coding & AlgorithmsTechnical Screen - 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 - SnapchatMediumMachine Learning EngineerDescribe a challenging project you led
This question evaluates leadership, project management, stakeholder communication, and technical problem-solving skills in a machine learning engineering context, with emphasis on trade-off analysis and impact measurement.
Behavioral & LeadershipTechnical Screen - 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 - SnapchatHardMachine Learning EngineerDesign a ranking system pipeline
This question evaluates competency in end-to-end ML system design for ranking and recommendation, covering problem definition, data and feature pipelines, offline training, online inference, model refresh, monitoring, and handling cold-start, exploration, feedback loops, and model drift.
ML System DesignTechnical Screen - 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 - SnapchatMediumMachine Learning EngineerDesign a short-video recommender for short-term interest
This problem tests your ability to design a real-time recommendation system that captures dynamic user intent over short sessions, balancing latency, feature freshness, and algorithmic relevance.
ML System DesignTechnical ScreenRecommender SystemsReal-time InferenceSession-based Models
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