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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 781–810 of 1311 results
- NetflixMediumSoftware EngineerDesign Ad Frequency and Order Tracking
This question tests the ability to design a high-throughput, low-latency distributed counter service for frequency capping and an accurate tracking system for ad order delivery.
System DesignOnsiteScalabilityDistributed SystemsCaching - NetflixMediumSoftware EngineerDesign Netflix viewport deduplication
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 Netflix viewport deduplication states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - NetflixHardSoftware EngineerDesign Publisher Configuration Rules
This question evaluates system design skills focused on configuration management and rule-based policy modeling for supply-side advertising platforms, covering inventory modeling, rule inheritance and overrides, conflict resolution, real-time evaluation, and operational controls like validation, versioning, rollout, and auditing.
System DesignOnsite - NetflixMediumSoftware EngineerDesign Rolling-Window Ad Frequency Capping
This question evaluates system-design skills for building scalable, low-latency services that enforce time-based rolling-window state, including data modeling for impression history, read/write paths, concurrency control, and fault tolerance; category: System Design.
System DesignOnsite - NetflixMediumSoftware EngineerDesign a Distributed Frequency-Capping Service
Tests the ability to design an ultra-low latency, highly available counting and rate-limiting system for ad frequency capping across distributed environments, balancing consistency with latency trade-offs.
System DesignOnsiteDistributed SystemsCachingAdTech - NetflixHardSoftware EngineerDesign a File Backup System
This question evaluates understanding of scalable system design, file synchronization and metadata handling, data consistency, fault tolerance, and performance trade-offs involved in designing a file backup system.
System DesignTechnical Screen - NetflixMediumSoftware EngineerDesign a Job Scheduler for ML Training and Batch Inference on a Shared Cluster
Design a job scheduler for machine learning workloads such as training runs and batch inference on a shared compute cluster with GPUs. It tests requirements gathering, queueing and fairness between teams, gang placement for distributed jobs, preemption and checkpointing, and recovery from node and scheduler failures.
System DesignTechnical Screen - NetflixMediumSoftware EngineerDesign a Scheduler for ML Training and Batch Inference Jobs
This question tests the ability to design a distributed job scheduler capable of handling heterogeneous ML workloads with varying priority, resource requirements, and fault-tolerance constraints.
System DesignOnsiteDistributed SystemsSchedulingResource Management - NetflixMediumSoftware EngineerDesign a Streaming Subscription System: Billing, Plan Changes and Payment Retries
Design the subscription backend of a video streaming service such as Netflix, covering the subscription lifecycle, recurring billing through an external payment provider, mid-cycle upgrades and downgrades, retries of failed charges, and scaling. It tests data modeling, safe payment handling, concurrency between member actions and billing jobs, and keeping entitlement checks fast.
System DesignOther - NetflixEasySoftware EngineerDesign a crash-resilient file system
This question evaluates understanding of durable storage and crash recovery mechanisms in file system design, including metadata consistency, durability guarantees, and operational concerns like performance and space overhead.
System DesignTechnical Screen - NetflixMediumSoftware EngineerDesign ad frequency capping
This question evaluates a candidate's competence in large-scale system design, including distributed systems, real-time analytics, data modeling, and consistency and scalability trade-offs for ad frequency capping.
System DesignOnsite - NetflixHardSoftware EngineerDesign ads frequency capping service
This question evaluates a candidate's ability to design a low-latency, high-QPS, multi-tenant frequency capping service, testing competencies in identity resolution, hierarchical cap modeling, window semantics, counter and storage architecture, consistency versus latency trade-offs, real-time decisioning APIs, configuration/versioning, backfill, reporting, privacy/compliance, and failure handling. It is commonly asked to assess systems-design proficiency in distributed systems, databases, caching, API design, and operational reliability; it belongs to the System Design domain and emphasizes practical application with system-level conceptual reasoning rather than purely algorithmic detail.
System DesignOnsite - NetflixHardSoftware EngineerDesign an Ad Pacing System
This question evaluates a candidate's skill in designing large-scale, low-latency distributed advertising systems, including pacing algorithms, budgeting and spend tracking, concurrency control, event processing, and observability.
System DesignOnsite - NetflixHardSoftware EngineerDesign an ad frequency capping system
This question evaluates competency in distributed systems architecture, real-time stateful services, high-cardinality time-series data modeling, API design for low-latency decision paths, and operational monitoring including consistency and latency trade-offs.
System DesignOnsite - NetflixHardSoftware EngineerDesign an ads audience targeting system
This problem evaluates your ability to design a high-scale, low-latency system for filtering user profiles against complex, dynamic advertising audience segments.
System DesignTechnical ScreenScalabilityDistributed SystemsCaching - NetflixMediumSoftware EngineerDesign an ads data model
This problem tests your ability to design a scalable, reliable data schema for an advertising platform that must support high-throughput event ingestion and real-time analytical queries.
System DesignOnsiteData ModelingScalabilityOLTP vs OLAP - NetflixHardData EngineerDesign config rollout and click aggregation
This problem tests your ability to design a global configuration distribution system combined with a high-throughput event processing pipeline to monitor rollout health.
System DesignOnsiteDistributed SystemsReal-time AnalyticsEvent Streaming - NetflixMediumSoftware EngineerDesign homepage viewport rendering with deduplication
This problem tests the ability to design a content-delivery service that optimizes viewport rendering through client-side requests, server-side deduplication, and efficient data retrieval patterns.
System DesignTechnical ScreenAPI DesignCachingHigh Availability - NetflixHardSoftware EngineerDesign viewport dedup for Netflix home page
Design viewport dedup for Netflix home page 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 - NetflixMediumSoftware EngineerModel ads demand data for reporting
This question tests the ability to design a robust data pipeline and schema for tracking ad performance metrics, focusing on handling event-level data, aggregations, and dimension consistency.
System DesignOnsiteData EngineeringData ModelingETL - NetflixMediumSoftware EngineerModel data for an ads platform
This question evaluates proficiency in data modeling and database schema design for advertising systems, including entity-relationship modeling, privacy-aware user identifier handling, and delivery/tracking log representation.
System DesignOnsite - New RelicMediumBackend EngineerDesign a Kafka Consumer Service That Groups Trace Events by Trace ID
Design a distributed service that consumes trace events from Kafka, groups every event sharing a trace ID, and hands each complete trace to an existing processing function. Covers partitioning, in-memory versus external state, deciding when a trace is complete, and traces that stay open for hours.
System DesignOnsite - NextdoorHardSoftware EngineerDescribe CAP, distributed systems, multithreading experience
This question evaluates practical and theoretical competence in the CAP theorem, distributed system architecture, and multithreaded concurrency, covering consistency models, partition tolerance, fault tolerance, scaling strategies, synchronization primitives, and debugging/performance techniques.
System DesignHR Screen - NextdoorHardData EngineerDesign KPI dashboard tables: retention, weekly rollups, timezone
This Nextdoor data engineer system design screen asks you to design the analytical data model and incremental ETL behind a fast, large-scale KPI dashboard for a photo-sharing app. It covers derived aggregate table design (grain, keys, partitioning), DAU/new-user/new-photo and follower-distribution metrics, 7-day deltas, then extends to week-1 cohort retention, weekly rollups, and switching the reporting timezone. The focus is correctness, performance at scale, and maintainability with timezone handled as a reporting parameter.
System DesignTechnical Screen - NextdoorMediumSoftware EngineerDesign a Job Scheduler That Can Scale by 100 Times
Design a distributed, asynchronous job scheduler that starts at modest traffic but can seamlessly scale up 100x. Evaluates API design, data storage trade-offs, worker coordination, task deduplication, and failure handling across scale boundaries.
System DesignTechnical ScreenDistributed SystemsJob SchedulerScalability - NextdoorMediumSoftware EngineerDesign a Neighborhood Newsfeed System
Design a privacy-aware, hyperlocal social feed that serves real-time updates and emergency alerts based on strict neighborhood boundaries.
System DesignTechnical ScreenFeed ArchitectureGeospatialDistributed Systems - NextdoorMediumSoftware EngineerDesign a Scalable Job Scheduler
This question evaluates system design skills focused on job scheduling, distributed systems concerns (state modeling, retries, idempotency), API and data-model design, fault tolerance, observability, and scalability within the System Design domain.
System DesignTechnical Screen - NielsenMediumSoftware EngineerDesign a URL Shortening Service: Code Generation, Storage and Fast Redirects
A system design question on building a URL shortening service that turns long links into short codes and redirects visitors quickly at large scale. It tests requirement scoping, capacity estimates, collision-free code generation across servers, storage and caching choices, and how the redirect path behaves under failure.
System DesignOther - NooksMediumSoftware EngineerHow would you throttle a crawler?
This question evaluates competency in scalable distributed system design, including rate limiting, request scheduling, concurrency control, fault tolerance, backoff/retry strategies, deduplication, and observability for networked crawlers.
System DesignOnsite - NotionMediumSoftware EngineerDesign a Shared Calendar Service
This problem tests the ability to design a scalable shared calendar system with support for recurring events, granular permission models, and notification scheduling.
System DesignOnsiteDatabase SchemaScalabilityAsynchronous Processing
Netflix
Nextdoor
Nielsen
Notion