practice a little every day, paws crossed ♡
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 2971–3000 of 9403 results
- DoorDashMediumSoftware EngineerDesign a Durable DAG Workflow for Order Refunds
This problem tests the ability to architect a robust, fault-tolerant workflow engine capable of managing complex state transitions and ensuring transactional integrity in distributed systems.
Software Engineering FundamentalsOnsiteSystem DesignDistributed SystemsWorkflow Engine - DoorDashMediumSoftware EngineerDesign a Food Item Review and Customer Reward System for a Delivery App
A DoorDash system design prompt to build a food item review system for a delivery app that also rewards customers for reviewing. It tests product judgment on open questions, verified-purchase writes, cached rating aggregates, and designing a practical, abuse-resistant reward program with reliable crediting.
System DesignOnsite - DoorDashMediumSoftware EngineerDesign a Food Rating System
This problem tests your ability to design a distributed, read-heavy rating and review system that handles high concurrency and ensures data integrity.
System DesignOnsiteDistributed SystemsCachingAPI Design - DoorDashMediumSoftware EngineerDesign a Food Review Platform
Design a food review platform for discovery, ratings, review text, optional dish-level content, and trusted aggregates. Define entity and review contracts, search and read paths, moderation, abuse resistance, privacy, scaling, and operational recovery.
System DesignOnsite - DoorDashHardSoftware EngineerDesign a Food Review System for a Delivery App, Focused on the Database Schema
System design question for the review feature of a food-delivery platform, where customers rate and review the food from delivered orders and others browse ratings. The focus is database schema design: tables, keys, constraints, indexes, rating aggregates, and how edits, deletes and moderation keep them correct.
System DesignOnsite - DoorDashMediumSoftware EngineerDesign a Food Review and Voting System
Design a scalable review and voting platform for dishes and restaurants, focusing on transactional vote changes, aggregate counter consistency, hot-item read/write scaling, and stable pagination.
System DesignOnsiteDistributed SystemsDatabasesCaching - DoorDashHardSoftware EngineerDesign a Food-Item Review System
Design an item-level review and rating platform for food delivery that handles high-throughput reads, asynchronous sentiment and moderation pipelines, and near real-time score aggregations.
System DesignOnsiteDistributed SystemsData ModelingCaching - DoorDashHardData ScientistDesign a Homepage Store Recommender
This question assesses the ability to design an end-to-end, low-latency recommendation system for a food delivery marketplace, focusing on candidate retrieval strategies, real-time personalization, and system architecture.
Machine LearningOnsiteRecommender SystemsSystem DesignRanking - DoorDashHardData ScientistDesign a Low-Latency Store Recommender
This question assesses the ability to architect a multi-stage recommendation pipeline that balances low-latency retrieval with high-accuracy ranking in a geo-aware, high-concurrency food delivery context.
Machine LearningOnsiteSystem DesignRecommendation SystemsLatency - DoorDashMediumSoftware EngineerDesign a Menu Item Review and Rating System for a Food-Delivery Platform
A system design question on a menu review feature for a food-delivery platform, where customers rate and review the menu items they ordered. It tests requirement prioritization, detailed review schema and API design, rating aggregation, caching and moderation, and time management that still reaches a deep dive.
System DesignOnsite - DoorDashHardSoftware EngineerDesign a Multi-Service Workflow Engine
Design a resilient, distributed workflow orchestration engine capable of executing multi-step business processes across heterogeneous services with strict guarantees around durability, idempotency, and failure recovery.
System DesignOnsiteDistributed SystemsSaga PatternWorkflow Engine - DoorDashEasySoftware EngineerDesign a Real-Time Monitoring System
This problem tests your ability to design a high-throughput observability pipeline capable of ingesting, storing, and alerting on time-series metrics from a distributed fleet of services.
System DesignOnsiteObservabilityTime-SeriesDistributed Systems - DoorDashMediumSoftware EngineerDesign a Refund Workflow as a Directed Acyclic Graph
Design a resilient, stateful workflow orchestration engine to process complex order refunds as a Directed Acyclic Graph (DAG), ensuring idempotency, crash recovery, and financial consistency.
System DesignOnsitesystem-designdistributed-systemsworkflow-engine - DoorDashMediumSoftware EngineerDesign a Resilient Bootstrap API Aggregator
Design a resilient bootstrap aggregation service that fetches critical initial state for a mobile app on launch. Tests interface design, concurrent I/O, partial failure handling, and operational trade-offs.
Software Engineering FundamentalsTechnical ScreenAPI DesignConcurrencyResilience - DoorDashMediumSoftware EngineerDesign a Review and Rating System for Food Delivery Menu Items
Design a review and rating system for a food-delivery platform, where customers review the individual menu items they received and every menu shows each item's rating. It tests data modeling, purchase verification, incremental rating aggregation, caching for read-heavy menus, moderation, and handling bursts on popular items.
System DesignOnsite - DoorDashMediumSoftware EngineerDesign a Sliding-Hour Top-Restaurants Service
This problem tests the ability to design a high-throughput, real-time analytics system that maintains a top-k leaderboard over a sliding time window.
System DesignOnsiteStreamingAnalyticsDistributed Systems - DoorDashMediumSoftware EngineerDesign a Store Recommendation System and Explain ML Trade-offs
Design a personalized store recommendation feed for an on-demand delivery platform and evaluate key machine learning modeling trade-offs.
ML System DesignOnsiteRecommendation SystemsMulti-Task LearningRanking - DoorDashEasyData ScientistDesign a Top Dasher experiment with interference
This problem tests your ability to design a controlled experiment in a marketplace with network effects, specifically focusing on how to mitigate spillover interference between treated and control groups.
Analytics & ExperimentationOnsiteExperimentationCausal InferenceMarketplace - DoorDashHardSoftware EngineerDesign a distributed cron job scheduler
Design a distributed cron job scheduler 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 - DoorDashMediumSoftware EngineerDesign a donations service with 3-day rolling totals
This question evaluates a candidate's competency in designing scalable, low-latency streaming data systems, covering event-time windowing, rolling-window aggregation, idempotency for duplicate events, late/out-of-order handling, and auditability.
System DesignOnsite - DoorDashMediumSoftware EngineerDesign a hierarchical path registry
Design a hierarchical path registry evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsOnsite - DoorDashMediumSoftware EngineerDesign a multi-channel notification system
This System Design question evaluates distributed-systems and API-design skills—scalability, reliable fanout, multi-channel integration, delivery guarantees (retries, idempotency, deduplication), rate-limiting, subscription/preferences modeling, and observability.
System DesignOnline Assessment - DoorDashHardSoftware EngineerDesign a notification system
This question evaluates a candidate's competency in designing scalable, reliable multi-channel notification platforms, covering distributed systems, multitenancy, API and storage schema design, queuing and retry strategies, rate limiting, observability, localization, A/B testing, and compliance considerations like GDPR.
System DesignTechnical Screen - DoorDashMediumSoftware EngineerDesign a resilient bootstrap API
This question evaluates skills in resilient API aggregation, fault-tolerant microservice orchestration, and reliability engineering, focusing on defining API contract semantics and handling partial failures at the architectural/system-design level (service-to-service abstraction); category/domain: System Design.
System DesignTechnical Screen - DoorDashHardSoftware EngineerDesign a resilient dasher payment system
A DoorDash software-engineer system-design interview question: design a resilient Dasher payment system that computes payouts from order lifecycle events (accept/fulfill/cancel). It spans event-driven ingestion, idempotency and exactly-once-vs-at-least-once semantics, data modeling for high write throughput and per-dasher pay-period queries, timezone/DST handling, detection and remediation of missing or out-of-order data, batch-vs-streaming reconciliation, reliability, and consistency trade-offs.
System DesignTechnical Screen - DoorDashHardSoftware EngineerDesign a scalable Instagram-like platform
Design a scalable Instagram-like platform 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 - DoorDashMediumMachine Learning EngineerDesign a scalable recommendation serving system
This question evaluates an engineer's ability to design scalable, low-latency, and resilient online recommendation serving infrastructure, emphasizing caching strategies, partitioning/sharding, data storage consistency, and observability.
System DesignOnsite - DoorDashHardSoftware EngineerDesign a service aggregator with robust error handling
Design a service aggregator with robust error handling 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 - DoorDashMediumSoftware EngineerDesign a single-machine LRU cache
This question evaluates a candidate's ability to design an efficient in-memory LRU cache and apply concurrency control, covering eviction semantics, capacity management, key updates, and synchronization for thread safety.
Coding & AlgorithmsTechnical Screen - DoorDashMediumSoftware EngineerDesign an API for pay computation with retries
Assesses the candidate's ability to design robust HTTP APIs covering endpoint modeling, request/response schemas, datetime formats, idempotency strategies, retry semantics, validation/error codes, and observability for pay-computation services.
Software Engineering FundamentalsOnline Assessment
DoorDash