Katkat

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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 6871–6900 of 9403 results

  • PinterestMediumSoftware Engineer
    Design Blackjack Hands, Splits, and a Multi-Deck Shoe

    This problem tests object-oriented design principles, specifically the ability to model a card game with multiple decks, complex state transitions (like splitting), and encapsulation of game rules.

    Software Engineering FundamentalsTechnical ScreenObject-Oriented DesignSystem ModelingGame Logic
  • PinterestHardSoftware Engineer
    Design Bulk CSV and Individual Record Updates with Reliable, Partitioned Processing

    A system design question about letting customers update records individually and in bulk by uploading CSV files. It focuses on reliable asynchronous job processing, idempotent row application, partitioning large files and the underlying data, conflicts between the two write paths, and reporting row outcomes.

    System DesignOnsite
  • PinterestHardSoftware Engineer
    Design Comment Notifications with Viral-Pin Aggregation

    Tests end-to-end system design for large-scale, bursty notification pipelines, focusing on stream processing, aggregation under viral traffic spikes, and reliable third-party push delivery.

    System DesignOnsiteDistributed SystemsStream ProcessingMessage Queues
  • PinterestMediumData Scientist
    Design Data Structure for Sparse Matrices Operations

    This question evaluates a candidate's ability to design efficient data structures and implement algorithms for sparse matrix storage and operations, emphasizing space-efficient representations, matrix arithmetic, and computational complexity reasoning.

    Coding & AlgorithmsOnsite
  • PinterestMediumMachine Learning Engineer
    Design Detection Systems for Risk and Safety

    This question tests the ability to design an end-to-end classification system for detecting harmful content (e.g., spam or toxic images) while balancing precision and recall at scale.

    ML System DesignOnsiteComputer VisionNLPContent Moderation
  • PinterestMediumMachine Learning Engineer
    Design Hierarchical Permission Checks

    This question evaluates understanding of hierarchical access control, tree data structures, and permission inheritance, testing competencies in data modeling and algorithmic reasoning.

    Coding & AlgorithmsTechnical Screen
  • PinterestHardSoftware Engineer
    Design Individual and Bulk Merchant Product Updates with Image Uploads

    This problem tests the ability to design a distributed system capable of handling high-throughput asynchronous updates, atomic transactional integrity for partial batch failures, and robust image processing pipelines.

    System DesignOnsiteAsynchronous ProcessingConcurrencyScalability
  • PinterestHardSoftware Engineer
    Design Pin recommendation system

    This question evaluates ability to design a large-scale personalized home feed recommendation system, testing skills in ML system design, recommender algorithms, retrieval and ranking architectures, feature engineering, data pipelines, low-latency serving, evaluation metrics, safety, and privacy.

    ML System DesignOnsite
  • PinterestHardSoftware Engineer
    Design Real-Time Search Autocomplete with Top-10 Popularity-Ranked Prefix Suggestions

    Design a distributed search autocomplete system capable of returning the top 10 popularity-ranked queries for any prefix with sub-30ms latency. The problem evaluates your ability to handle massive read throughput, partition heavily skewed prefix workloads, and merge streaming popularity signals with batch historical baselines.

    System DesignOnsiteDistributed SystemsSearchCaching
  • PinterestMediumMachine Learning Engineer
    Design User and Item Embeddings from Long Histories

    Design an end-to-end candidate retrieval system using user and visual-item embeddings capable of processing ultra-long user histories (up to 160,000 interactions) while handling real-time freshness, cold-start items, and privacy constraints.

    ML System DesignOnsiteRecommendation SystemsVector EmbeddingsCandidate Retrieval
  • PinterestMediumSoftware Engineer
    Design a Distributed Rate Limiter

    This problem evaluates your ability to design a distributed rate-limiting service that maintains low latency while enforcing consistent request quotas across multiple global nodes.

    System DesignTechnical ScreenDistributed SystemsCachingConcurrency
  • PinterestMediumSoftware Engineer
    Design a Distributed Rate-Limiting Service

    Design a highly available, ultra-low-latency distributed rate-limiting service supporting multi-tier rules (user, tenant, route, global) across globally distributed edge gateways.

    System DesignOnline Assessmentsystem-designdistributed-systemsrate-limiting
  • PinterestHardSoftware Engineer
    Design a Google Photos–like service

    This question evaluates proficiency in designing large-scale distributed media systems, testing competencies in distributed storage and caching, ingest pipelines, CDN-backed delivery, indexing/search, sync/conflict resolution, access control/privacy compliance, and cost/operational planning.

    System DesignOnsite
  • PinterestMediumSoftware Engineer
    Design a Large-File Upload and Analysis Flow

    Tests the ability to design an end-to-end media ingestion system supporting chunked resumable uploads, asynchronous analysis pipelines, idempotency, and real-time client notifications.

    System DesignOnsitesystem-designcloud-storagedistributed-systems
  • PinterestMediumSoftware Engineer
    Design a Low-Latency Typeahead Service

    This problem tests the ability to design a high-throughput, low-latency search suggestion system that handles real-time updates and ranking at scale.

    System DesignOnsiteCachingDistributed SystemsSearch
  • PinterestHardSoftware Engineer
    Design a Merchant Catalog Update Pipeline with Bulk Files and Image Resizing

    Tests the ability to architect a scalable, asynchronous catalog ingestion pipeline that balances high-throughput bulk feed processing with low-latency single-item edits while prioritizing price and inventory updates over compute-heavy image processing.

    System DesignOnsiteDistributed SystemsData PipelinesMessage Queues
  • PinterestMediumSoftware Engineer
    Design a Multi-Channel Notification System

    Design an extensible, resilient multi-channel notification engine (push, email, SMS, in-app) supporting high throughput, deduplication, quiet hours, rate limiting, and provider fallbacks.

    System DesignOnline Assessmentsystem-designdistributed-systemsevent-driven
  • PinterestHardSoftware Engineer
    Design a Typeahead Service on an In-Memory Trie, Then Scale It Without New Services

    Design a typeahead autocomplete service that starts at a modest scale using an in-memory keyword trie, then scale it out without adding external services. It tests trie internals and keyword storage, read and write paths, score updates, rebuilds with hot swaps, and sharding strategy trade-offs.

    System DesignOnsite
  • PinterestEasySoftware Engineer
    Design a Typeahead Suggestion System

    Design a low-latency, real-time typeahead suggestion system that handles prefix search, query ranking, aggressive caching, and stale response mitigation.

    System DesignOnsitesystem-designtrietypeahead
  • PinterestHardSoftware Engineer
    Design a high-throughput distributed rate limiter

    Pinterest software-engineer onsite system-design question: design a multi-region, high-throughput distributed rate limiter targeting ~10M req/s with per-user, per-API, and global limits, burst tolerance, and an approximately-sliding window. It tests token-bucket/GCRA algorithm choice, an architecture of local in-process buckets fed by epoch-based token leases, consistent-hashing sharding with hot-key splitting, bounded-overshoot consistency, fault handling, fairness, capacity-planning math (including a 2× spike), backpressure, and observability.

    System DesignOnsite
  • PinterestHardMachine Learning Engineer
    Design a real-time home feed ranker

    This problem evaluates your ability to design a multi-stage recommendation architecture capable of integrating real-time user signals, managing feature latency, and balancing ranking accuracy with system throughput.

    ML System DesignOnsiteSystem DesignRecommendation SystemsReal-time
  • PinterestMediumSoftware Engineer
    Design a violation log analyzer

    This question evaluates proficiency in data structures, in-memory indexing and query design, algorithmic time/space complexity analysis, and reasoning about state management for dynamic event streams.

    Coding & AlgorithmsTechnical Screen
  • PinterestMediumSoftware Engineer
    Design adjustable ID allocator

    A Pinterest software-engineer onsite coding problem: design an adjustable ID allocator over a fixed [0, 999] ID space with named, contiguous, non-overlapping bucket ranges. It covers initial allocation (packing from desired sizes and validating/normalizing proposed ranges), a resize operation that grows or shrinks a bucket by consuming adjacent free space and then minimally shifting or borrowing from neighbors under a deterministic policy, plus complexity analysis, boundary-case testing, and concurrency handling.

    Coding & AlgorithmsOnsite
  • PinterestHardSoftware Engineer
    Design an Ad Click Aggregator for Last-Year Counts Using an Existing Logging API

    A system design question about an ad click aggregator whose queries cover the last year rather than the last few minutes and which must take its click data from an existing logging API. It tests requirement clarification, checkpointed ingestion and backfill, deduplication, rollup storage, and correcting historical counts.

    System DesignOnsite
  • PinterestMediumSoftware Engineer
    Design an ads event reporting system

    This question tests the ability to design a high-throughput, fault-tolerant system for tracking ad interaction events, focusing on scalability, exactly-once processing, and analytical query performance.

    System DesignOnsiteScalabilityData PipelinesAnalytics
  • PinterestHardMachine Learning Engineer
    Design an ads system to improve CTR

    This question evaluates machine learning system design competency for improving ad click-through rate, testing understanding of metrics, end-to-end architecture, training data and embeddings, and operational issues like cold start, bias and delayed feedback within advertising and recommender domains.

    ML System DesignTechnical Screen
  • PinterestHardMachine Learning Engineer
    Design an unsafe content detection system

    This problem evaluates your ability to design a scalable, multimodal machine learning pipeline for detecting policy-violating content on a large-scale visual discovery platform.

    ML System DesignOnsiteMultimodal LearningReal-time InferenceContent Moderation
  • PinterestMediumData Scientist
    Design and Evaluate a Home Carousel

    This question evaluates a candidate's expertise in product analytics, experimentation design, metric definition, and instrumentation for measuring the impact of a new UI feature.

    Analytics & ExperimentationTechnical Screen
  • PinterestHardData Scientist
    Design and Interpret a Video Pin Experiment

    This question tests the ability to design a balanced A/B experiment for a two-sided marketplace (creators and viewers) and synthesize conflicting metrics into a launch decision.

    Analytics & ExperimentationTechnical ScreenA/B TestingProduct MetricsGuardrails
  • PinterestMediumData Scientist
    Design and assess a video-pin increase experiment

    A Pinterest Data Scientist technical-screen question on Analytics & Experimentation: design a rigorous A/B test for increasing video-pin share in the Home Feed — unit of randomization, primary metric and guardrails, power/MDE, sequential analysis, and a quasi-experiment fallback — then interpret two 14-day readouts and recommend ship, iterate, or stop. It rewards balancing engagement lifts (CTR) against guardrail regressions (retention, complaints, crash rate), multiple-testing robustness, and cross-unit (per-impression vs per-session) trade-offs.

    Analytics & ExperimentationTechnical Screen