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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
- Languages
Showing 661–690 of 721 results
- TeslaMediumSoftware EngineerDesign a Video Sharing Platform
Design a resilient, large-scale video sharing and streaming platform that handles multi-gigabyte uploads, asynchronous transcoding, and low-latency global delivery. This question tests your ability to design chunked upload protocols, idempotent processing pipelines, and CDN-backed adaptive streaming architectures.
System DesignOnsiteDistributed SystemsVideo StreamingCDN - TeslaMediumSoftware EngineerDesign an Order Fulfillment System
Design an order-fulfillment system and explain its major components, data flow, and reliability trade-offs.
System DesignOnsite - TeslaMediumBackend EngineerDesign booking and settlement systems
This question evaluates backend system design competencies such as concurrency control, transactional integrity, reconciliation, file ingestion and processing, idempotency, API design, and operational reliability.
System DesignOnsite - TeslaHardSoftware EngineerFrom a Monorepo Commit to an Over-the-Air Vehicle Update, and Choosing What to Build
Trace everything that happens between an engineer pushing a commit to a monorepo and the resulting software being installed on customers' cars, then explain how the monorepo decides which targets to build and test and in what order. It tests CI and release gating, artifact provenance, staged over-the-air rollout, safe in-vehicle installation, and dependency-graph builds.
System DesignOnsite - TikTokHardSoftware EngineerExplain Your System Architecture
Explain Your System Architecture 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 DesignOnsite - TruefoundryMediumSoftware EngineerDesign Interviewer Availability and Atomic Booking APIs
Design a relational data model and concurrent APIs for managing interviewer availability and atomic candidate interview booking.
System DesignOnsiteConcurrencyDatabase DesignAPI Design - UberHardSoftware EngineerCompare Paxos and Raft
This question evaluates understanding of distributed consensus protocols, replicated logs, linearizability, fault tolerance, and operational concerns such as leader election, quorum semantics, log replication, membership changes, and failure recovery.
System DesignOnsite - UberMediumSoftware EngineerDesign A URL Shortener
This question tests your ability to design a high-scale, distributed URL shortening service that handles billions of requests while ensuring low latency and data durability.
System DesignOnsiteDistributed SystemsCachingScalability - UberHardSoftware EngineerDesign Distributed Storage for Large Structured Data
Design distributed storage with versioned metadata, block replicas, layered caches, failure repair, locality-aware jobs, and resource-aware load balancing.
System DesignOnsite - UberHardSoftware EngineerDesign Food Delivery Cart
This question tests the ability to design a distributed, highly concurrent shopping cart service for a food delivery platform, focusing on transactional integrity, race conditions, and eventual consistency.
System DesignOnsiteConcurrencyDistributed SystemsCaching - UberMediumSoftware EngineerDesign MapReduce for schedule aggregation
Design MapReduce for schedule aggregation 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 DesignOnsite - UberHardSoftware EngineerDesign MapReduce for schedules
This question evaluates proficiency in scalable stream and batch data processing, windowed aggregation, event-time semantics, deduplication, skew mitigation, and distributed computation using MapReduce/Spark paradigms; it falls under System Design and Big Data/stream-processing and is commonly asked to assess designing correct, high-throughput windowed aggregations and handling late or duplicated events at scale. The level of abstraction is practical application with architectural and operational considerations rather than low-level coding, and this English summary frames the competency and interview focus for search engines.
System DesignOnsite - UberMediumSoftware EngineerDesign Product Page View Tracking
This question evaluates a candidate's ability to design scalable, reliable event-collection and analytics systems, covering client- and server-side instrumentation, event schemas/APIs, counting total versus unique views, handling high write volumes for popular products, storage choices for raw events and aggregated counters, and operational concerns such as bot filtering, deduplication, privacy, fraud prevention, freshness, reliability, and monitoring. It is commonly asked in the System Design domain to assess architectural thinking and operational trade-offs, testing both conceptual understanding of distributed systems and practical application of scalable data pipelines, storage, and observability.
System DesignOnsite - UberHardSoftware EngineerDesign Uber Eats-style search function
An Uber Software Engineer system design onsite question: design the search function for an Uber Eats-style food delivery platform, covering APIs, data ingestion, geo-aware indexing and retrieval, multi-stage ranking, real-time availability updates, scaling, caching, fault tolerance, monitoring, and freshness-vs-latency trade-offs. It tests the ability to build a low-latency, location-aware, highly available search system with strong observability.
System DesignOnsite - UberMediumSoftware EngineerDesign a Distributed Logging System
This problem evaluates the ability to design a high-throughput, fault-tolerant logging infrastructure capable of ingesting and storing massive volumes of telemetry data from diverse distributed services.
System DesignOnsiteDistributed SystemsScalabilityData Pipeline - UberMediumSoftware EngineerDesign a Driver Leaderboard Based on Reviews
This problem tests the ability to design a scalable, low-latency leaderboard system that handles high-frequency write throughput from reviews and supports read-heavy leaderboard queries.
System DesignOnsiteScalabilityCachingData Modeling - UberMediumSoftware EngineerDesign a Food Delivery Cart
This question tests the ability to design a distributed, low-latency, and fault-tolerant shopping cart service for a high-concurrency food delivery platform.
System DesignOnsiteDistributed SystemsAPI DesignCaching - UberMediumSoftware EngineerDesign a Highly Available URL Shortener
This question tests your ability to design a distributed, highly available system that handles high-read traffic and ensures data integrity for short-URL mappings.
System DesignOnsiteScalabilityCachingDatabases - UberMediumSoftware EngineerDesign a Real-Time Chat System
This question tests the ability to design a highly available and scalable real-time chat service, focusing on persistent connections, message routing, and reliable delivery mechanisms.
System DesignOnsiteWebSocketsDistributed SystemsScalability - UberMediumSoftware EngineerDesign a Real-Time Nearby-Driver Service
Tests the ability to architect a high-throughput, low-latency geospatial ingestion and query service that tracks millions of moving entities, handles state transitions, and avoids boundary/hot-spot bottlenecks.
System DesignOnsiteGeospatialDistributed SystemsIn-Memory Caching - UberHardSoftware EngineerDesign a ride-hailing platform like Uber
This question evaluates a candidate's competency in large-scale system design, covering distributed systems architecture, data modeling, real-time location streaming, matching algorithms, scalability, fault tolerance, and secure payment handling.
System DesignOnsite - UberHardSoftware EngineerDesign a search autocomplete system
This system design question evaluates the ability to architect a large-scale search autocomplete service, testing knowledge of prefix data structures, distributed indexing, and latency-sensitive serving pipelines. It is commonly asked in senior engineering interviews to assess trade-off reasoning between freshness, read performance, and system complexity at scale.
System DesignOnsite - UberMediumSoftware EngineerDesign cart and pricing engine classes
This question evaluates object-oriented system design and domain modeling skills related to cart operations, item customizations, composable pricing rules (surge, promotions, membership) and producing an itemized receipt.
System DesignOnsite - UberHardSoftware EngineerDesign driver heat map and discuss consensus
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 driver heat map and discuss consensus states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignOnsite - UberHardSoftware EngineerDesign real-time driver heatmap system
This question evaluates a candidate's ability to design real-time distributed systems for geospatial aggregation, covering skills in spatial partitioning, high-throughput streaming ingestion, low-latency cell counting, WebSocket-based client updates, and top-K ranking within a fault-tolerant multi-region architecture.
System DesignOnsite - UberHardSoftware EngineerDesign the Data Flow Behind a Food Delivery App's Restaurant List
A system design interview question asking you to design the data flow behind a food delivery app's restaurant list for a customer's delivery address. It tests geographic indexing of delivery areas, propagating restaurant status and delivery-time changes, read-path latency, caching, and freshness trade-offs.
System DesignOnsite - UberMediumSoftware EngineerModel user-to-resource access permissions in a graph database and migrate to it
Design how to store and check which people can access which resources using a graph database, including the vertex and edge schema, access-check traversals, and scaling with caching and partitioning. It also covers migrating from the existing database without downtime, testing access modeling, bounded traversals and safe data migration.
System DesignOnsite - UberHardSoftware EngineerPrioritize rooms for allocation
This question evaluates a candidate's ability to design a real-time room allocation and ranking service in the System Design domain, testing competencies in architectural design, ranking and scoring functions, data sourcing and freshness, fairness mechanisms, and online evaluation and experimentation.
System DesignOnsite - Uber FreightMediumSoftware EngineerDesign a Distributed URL Shortener for Very High Redirect Traffic
A system design interview question asking you to design a distributed URL shortener. It tests API design, unique short-code and distributed ID generation, collision handling, storage and sharding, caching for very high redirect traffic, availability, fault tolerance, and link expiration.
System DesignOnsite - Uber FreightMediumSoftware EngineerDesign a Real-Time Restaurant Analytics Dashboard
This problem tests the ability to design a distributed, low-latency analytics pipeline capable of handling high-throughput event ingestion, time-windowed aggregations, and efficient cache retrieval.
System DesignOnsiteDistributed SystemsStreamingCaching
Tesla
TikTok
Uber
Uber Freight