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System Design 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
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- 546
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- 11
- Topics
- 8
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Showing 241–270 of 517 results
- LinkedInHardSoftware EngineerDesign a Multi-Region Malicious-IP Detection System
Design a globally distributed, low-latency edge security service that detects and blocks malicious IP addresses across regions, featuring decentralized evaluation, asynchronous intelligence sharing, and rapid false-positive rollback.
System DesignTechnical ScreenDistributed SystemsSecurityLow Latency - LinkedInMediumSoftware EngineerDesign a Top-K search words service
The question evaluates understanding of scalable, low-latency analytics and search-event systems, including high-throughput event ingestion, Top-K aggregation across all-time and sliding windows, normalization/deduplication trade-offs, and multi-region consistency considerations.
System DesignTechnical Screen - LinkedInHardMachine Learning EngineerDesign a distributed key-value store
Design a distributed key-value store evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - LinkedInHardSoftware EngineerDesign distributed parallel job processing
This question evaluates understanding of distributed systems architecture, parallel job scheduling, fault tolerance, coordination and concurrency control, API and data model design, idempotency, observability, and capacity planning for multi-tenant, heterogeneous workloads.
System DesignTechnical Screen - LinkedInMediumSoftware EngineerExplain database transactions and ACID
This question evaluates a candidate's understanding of database transactions including ACID properties, isolation levels (read uncommitted, read committed, repeatable read, serializable), common anomalies (dirty reads, non-repeatable reads, phantom reads), MVCC, and commit/rollback semantics, testing competency in transactional correctness and concurrency control. Commonly asked in System Design and database contexts because it probes reasoning about data integrity, visibility, and durability under concurrent workloads, and it tests both conceptual understanding of transactional guarantees and practical application of isolation behavior in relational database systems.
System DesignTechnical Screen - LinkedInHardSoftware EngineerReduce Stale Listings in a Job Marketplace
Design an auditable staleness-detection and remediation engine for a global job marketplace that aggregates heterogeneous signals, enforces graduated interventions, and supports low-latency employer appeals.
System DesignTechnical ScreenDistributed SystemsEvent-Driven ArchitectureAudit Logging - LinkedInEasySoftware EngineerReview a Web Application Architecture
This question evaluates system design competencies such as scalability, reliability, fault tolerance, database architecture, load balancing, external dependency management, and observability, and is categorized under System Design.
System DesignTechnical Screen - Lowe'sHardSoftware EngineerExplain cloud computing fundamentals
This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Explain cloud computing fundamentals states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - MercorMediumSoftware EngineerCheck-and-Insert for a Million User IDs: Balancing Latency, Memory and Accuracy
Design a check-and-insert service for about a million user IDs that reports whether an ID already exists and adds it if not. It tests memory estimates, data structure choice, atomic inserts under concurrency, trading memory for accuracy with compact filters, and durable on-disk storage with fast reads and writes.
System DesignTechnical Screen - MercorMediumSoftware EngineerDesign a Project-to-Contractor Matching System
Tests your ability to architect a two-sided matching platform that enforces strict eligibility filters, dynamic availability tracking, multi-stage ranking with exploration, and closed-loop model evaluation.
System DesignTechnical Screensystem-designmatching-enginerecommendation-systems - MercorEasyMachine Learning EngineerDesign a Social Feed
Design an end-to-end personalized social feed system capable of serving low-latency ranked content while handling hybrid fanout, multi-stage ML candidate retrieval, and stable pagination.
System DesignTechnical Screensystem-designfeed-rankingrecommendation-systems - MercorMediumSoftware EngineerDesign an API to Deep-Copy a Dataset with Its Tasks, Model Responses and Grades
A system design question about an API that copies a dataset together with its tasks, model responses and grades so that the copy can be edited independently. It covers ID remapping, background jobs with progress tracking and resumable checkpoints, idempotent requests, worker leases, edits to the source during the copy, and cleanup after failure.
System DesignTechnical Screen - MercorMediumSoftware EngineerExplain Kubernetes autoscaling and traffic routing
This question evaluates understanding of Kubernetes autoscaling mechanisms, external-to-pod traffic routing, and the differences between ReplicaSet and StatefulSet controllers.
System DesignTechnical Screen - MercorMediumSoftware EngineerMake a Charge-Then-Record Payment Endpoint Safe Against Timeouts, Retries and Crashes
A payment endpoint calls an external provider to charge the customer and then writes a record to its own database. The question asks what can go wrong and how to redesign the flow, testing failure analysis for crashes and timeouts, safe retries, durable payment state, recovery through status checks, webhooks and reconciliation, and lock placement.
System DesignTechnical Screen - MetaMediumSoftware EngineerDebug and optimize React performance issues
This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Debug and optimize React performance issues states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - MetaMediumData EngineerDefine metrics and data model for product features
This problem evaluates your ability to translate product goals into actionable metrics and design a scalable, reliable data schema to support those metrics.
System DesignTechnical ScreenData ModelingProduct AnalyticsMetrics - MetaMediumSoftware EngineerDesign Search And Web Crawling Systems
This question tests the ability to design a scalable web crawler capable of handling billions of pages while maintaining freshness and avoiding redundant work.
System DesignTechnical ScreenDistributed SystemsWeb CrawlingScalability - MetaHardSoftware EngineerDesign a bank system with scheduling and rankings
Design a bank system with scheduling and rankings evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - MetaMediumSoftware EngineerDesign a mini banking system
This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Design a mini banking system states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - MetaMediumSoftware EngineerDesign a ranking and recommendation system
This problem tests your ability to design a multi-stage recommendation pipeline that balances low-latency retrieval with high-precision ranking at scale.
System DesignTechnical ScreenMachine LearningRecommendation SystemsScalability - MetaMediumSoftware EngineerDesign a real-time ad impression aggregator
This question evaluates a candidate's ability in scalable real-time system design, covering competencies such as stream processing, event aggregation, time-windowed metrics, handling late and out-of-order events, and designing for very high write throughput.
System DesignTechnical Screen - MetaHardSoftware EngineerDesign a scalable banking system
This problem tests your ability to design a distributed, high-concurrency ledger system that maintains strict consistency and atomicity for financial transactions.
System DesignTechnical ScreenDistributed SystemsACIDDatabase Design - MetaMediumMachine Learning EngineerDesign a weapon-ad harmful content detection system
This question assesses the ability to architect a scalable, multi-modal machine learning pipeline for detecting policy-violating content (weapon advertisements) within a high-throughput ad-delivery system.
System DesignTechnical ScreenMulti-modal MLComputer VisionNLP - MetaHardSoftware EngineerDesign an Online Game Leaderboard
A Meta software-engineer system-design screen: design the backend for an online game leaderboard supporting score recording, a global top-N board, a friends board, a player's rank and nearby players, and daily/weekly/seasonal/all-time windows at high write volume and low read latency. The model answer separates a durable score event log from an in-memory sorted ranking store, computes the friends board on read, and covers tie-breaking, caching, sharding, consistency trade-offs, anti-cheat, and rebuilds.
System DesignTechnical Screen - MetaHardSoftware EngineerDesign input validation and error handling
A Meta software engineer system design technical screen: design the API and system-level input validation and error-handling strategy for a service that computes the top-k most frequent elements in a posted array. The merged answer covers the request/response contract with a worked example, payload and cardinality limits, layered validation across client, gateway and service, authentication, rate limiting, idempotency, timeouts and retries, the full 4xx/5xx error taxonomy with sample error responses, partial-failure modes, graceful degradation to approximate top-k with stated error bounds, defenses against compression bombs and poisoned payloads, observability, and a test and production monitoring plan.
System DesignTechnical Screen - MetaHardData EngineerDesign tables for event-driven metrics
This question evaluates relational data modeling and data engineering competencies for high-volume event analytics, including schema design, partitioning and clustering strategies, duplicate and late-arriving event handling, and normalization versus denormalization trade-offs.
System DesignTechnical 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 - MicrosoftMediumSoftware EngineerDesign A Scalable Web Crawler
This question evaluates scalable system architecture and distributed systems competencies, specifically testing web crawler concepts such as URL discovery and deduplication, scheduling and prioritization, politeness-aware fetching, parsing and link extraction, storage of content and metadata, failure handling, and monitoring.
System DesignTechnical Screen - MicrosoftMediumSoftware EngineerDesign a ChatGPT-like serving system
This question tests the ability to design a scalable, low-latency LLM inference system, focusing on request handling, KV-cache optimization, and horizontal scaling strategies.
System DesignTechnical ScreenLLMScalabilityInference - MicrosoftMediumSoftware EngineerDesign a To-Do List Service (CRUD, Auth, Rate Limiting, Caching & API Versioning)
This question tests the ability to design a scalable, multi-tenant To-Do service, focusing on API versioning, authentication, rate limiting, and data integrity.
System DesignTechnical ScreenAPI DesignCachingRate Limiting
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