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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 2941–2970 of 9403 results
- DoorDashMediumSoftware EngineerDebug Round-Robin and Consistent-Hash Routing
This problem tests the ability to identify flaws in load balancing implementations by evaluating consistency, distribution, and edge-case handling in Round-Robin and Consistent Hashing logic.
Software Engineering FundamentalsOnsiteLoad-BalancingConsistent-HashingDistributed-Systems - DoorDashMediumSoftware EngineerDebug a Random Dasher Registry
Debug a random dasher registry backed by a dense array and an ID-to-index map. Repair empty and swap-delete edge cases, preserve representation invariants, narrow error handling, and extend the design for concurrency and slow dependencies.
Software Engineering FundamentalsOnsite - DoorDashMediumSoftware EngineerDebug a Round-Robin Load Balancer, Then Implement Consistent Hashing
Debug a round-robin load balancer that must keep strict rotation while servers are added and removed, then implement a consistent-hash ring that gives each key a stable server. It tests off-by-one and index-mutation bugs, thread safety, stable hashing, virtual nodes, lookup cost, and how many keys move on membership changes.
Software Engineering FundamentalsOnsite - DoorDashHardSoftware EngineerDebug a cache incident end-to-end
This question evaluates a candidate's ability to diagnose and debug production cache incidents, testing competencies in distributed caching, observability, incident response, root-cause analysis, and the operational impact on microservice latency.
Software Engineering FundamentalsTechnical Screen - DoorDashMediumSoftware EngineerDebug a driver assignment bug
This question evaluates debugging, root-cause analysis, unit/integration test design, observability, and system-resilience competencies within the Coding & Algorithms domain, emphasizing practical skills in reproducing failures, isolating defects, and implementing targeted fixes.
Coding & AlgorithmsOnsite - DoorDashMediumSoftware EngineerDebug and refactor a legacy module
This question evaluates debugging, refactoring, naming and exception handling, input validation, code structure, and concurrency-safety design skills within a legacy codebase, requiring both hands-on code changes and higher-level reasoning about immutability, confinement, synchronization, and concurrent data structures.
Coding & AlgorithmsOnsite - DoorDashMediumSoftware EngineerDebug round-robin request router
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 round-robin request router states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - DoorDashMediumSoftware EngineerDebug round-robin, DashMap, and simple cache
This question evaluates skills in concurrent programming and stateful selection logic (round-robin load balancing), data structure invariants and debugging (custom hash map hashing vs equality, collision resolution, resizing and iterator correctness), simple in-memory caching strategies with TTL or size-based eviction, and unit test design.
Coding & AlgorithmsTechnical Screen - DoorDashHardSoftware EngineerDebug the Last-Element Random Allocation Case
Implement and test an O(1) randomized pool that avoids and deterministically tests against the classic self-swap regression when removing the tail element.
Software Engineering FundamentalsOnsiteHash TableDesignTesting - DoorDashMediumSoftware EngineerDebug using logs and allocate tasks
This question evaluates a candidate's skill in log-driven debugging, production incident investigation, and cross-functional task allocation, covering competencies such as structured and contextual logging, correlation identifiers, noise reduction, minimal reproducibility, feature-flagged isolation, triage coordination, hypothesis tracking, root-cause confirmation, regression prevention, and blameless postmortems. It is commonly asked to assess operational troubleshooting and teamwork under production uncertainty within the Coding & Algorithms category, testing practical application of debugging techniques alongside conceptual understanding of incident management and process-level coordination.
Coding & AlgorithmsOnsite - DoorDashHardData ScientistDecide and test a 20% discount strategy
This question tests the ability to design a controlled experiment to evaluate a promotional discount strategy, focusing on causality, profit optimization, and long-term customer value impact.
Analytics & ExperimentationOnsiteCausal InferenceExperimentationUplift Modeling - DoorDashHardData ScientistDecompose and optimize delivery operational costs
This question evaluates a data scientist's ability to decompose per-order operational costs, identify high-impact levers to reduce unit economics, and design rigorous experiments and monitoring for a two-sided delivery marketplace, testing competencies in cost modeling, causal inference, experimentation design, and product analytics.
Analytics & ExperimentationOnsite - DoorDashHardSoftware EngineerDeep-dive a project architecture
An open-ended DoorDash software-engineer system-design screen: pick a real project and deep-dive its architecture end to end. Candidates draw the diagram, state invariants, walk read/write paths, justify storage and trade-offs, capacity-plan, cover reliability/security/observability with SLOs, recount a real incident, and propose a quantified 10x-traffic plan. Includes a full worked example built around a real-time delivery dispatch and live order-tracking service.
System DesignTechnical Screen - DoorDashMediumSoftware EngineerDefend an Ownership Project with Measurable Impact
Tests an engineer's ability to demonstrate end-to-end ownership, justify architectural trade-offs under constraints, and prove business or operational impact using credible metrics.
Behavioral & LeadershipTechnical ScreenOwnershipSystem ArchitectureMetrics & Impact - DoorDashHardData ScientistDefine and compute retention and churn precisely
This question evaluates a Data Scientist's competency in statistical measurement of user retention and churn, covering cohort definition, activity rules, risk-set-aware retention and churn formulas, censoring and delayed conversion handling, and survival-analysis concepts like time-to-churn, hazard, and cumulative incidence.
Statistics & MathOnsite - DoorDashHardData ScientistDefine metrics for new market expansion success
This question tests the ability to design a comprehensive evaluation framework for entering a new geographic market by balancing growth, unit economics, and marketplace balance.
Analytics & ExperimentationOnsiteAnalyticsMarketplaceKPIs - DoorDashMediumSoftware EngineerDemonstrate leadership and team development
Demonstrate leadership and team development evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipTechnical Screen - DoorDashMediumSoftware EngineerDescribe a Project End-to-End
This question evaluates a candidate's ability to demonstrate end-to-end project ownership, technical decision-making, cross-functional communication, and measurement of business impact, and is commonly asked to assess how an individual explains their role, trade-offs, launch outcomes, and lessons learned.
Behavioral & LeadershipTechnical Screen - DoorDashMediumSoftware EngineerDescribe your most impactful recent project
A DoorDash software-engineering onsite behavioral question asking you to walk through your most impactful recent project: the problem, your specific role, measurable impact, a key technical decision and its trade-offs, how you handled scaling and reliability, a risk or failure you hit, and what you'd do differently. Includes a structured STAR-plus-deep-dive framework and a worked real-time-dispatch example.
Behavioral & LeadershipOnsite - DoorDashHardData ScientistDesign A/B Test to Evaluate Algorithm's Revenue Impact
DoorDash statistics and experimentation prompt on A/B testing a recommendation algorithm's revenue impact, covering hypotheses, randomization, sample size, heavy-tailed revenue, p=0.08 interpretation, and causal alternatives.
Statistics & MathTechnical Screen - DoorDashMediumSoftware EngineerDesign API that aggregates three downstream APIs
This question evaluates a candidate's ability to design an API aggregator, covering skills in service orchestration, fault tolerance, latency and SLO management, error handling, and observability for distributed HTTP/JSON services.
System DesignTechnical Screen - DoorDashMediumData ScientistDesign Biker metrics and A/B test plan
This question tests the ability to design an experimentation framework for a two-sided marketplace, focusing on metric definition, causal inference, and identifying potential gaming behaviors in delivery logistics.
Analytics & ExperimentationTechnical ScreenA/B TestingMarketplace AnalyticsMetric Design - DoorDashMediumData ScientistDesign Experiments to Measure Promotion Scheduling Impact
This interview question evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer for Design Experiments to Measure Promotion Scheduling Impact states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Analytics & ExperimentationOnsite - DoorDashMediumSoftware EngineerDesign Food Ratings and Driver Payouts
This question evaluates system design competencies such as API design, data modeling and storage selection for aggregated 5-point ratings, handling user-generated posts and likes, service decomposition, consistency trade-offs, scalability, and designing a monthly batch payout pipeline for driver earnings.
System DesignOnsite - DoorDashMediumSoftware EngineerDesign Food-Item Reviews, Ratings, and Mutable Vote Counts
Design item reviews and votes with purchase eligibility, unique reviews, rating aggregates, reliable counters, pagination, and recoverable caching.
System DesignOnsite - DoorDashHardSoftware EngineerDesign Real-Time Driver Pay Aggregation
This question evaluates competence in designing scalable, fault-tolerant streaming systems and implementing correct time-windowed aggregation logic, testing skills in distributed systems, stream processing, and data correctness; it belongs to the system design domain and streaming/real-time data engineering and spans both conceptual architectural thinking and practical application-level concerns. It is commonly asked to probe reasoning about correctness under at-least-once delivery and messy inputs (out-of-order, duplicate, late, or malformed events), operational resilience, and trade-offs between throughput, latency, and auditability in production-scale pipelines.
System DesignTechnical Screen - DoorDashHardSoftware EngineerDesign a 3-day donation platform
This question evaluates competency in designing scalable, highly available payment-enabled distributed systems, including skills in traffic spike handling, idempotency and reconciliation, real-time totals and leaderboards, latency and throughput planning, and compliance/privacy considerations.
System DesignOnsite - DoorDashMediumSoftware EngineerDesign a Customer Review Page
This question tests the ability to design a scalable review system capable of handling high-write volume, media storage, and efficient retrieval with pagination.
System DesignTechnical ScreenAPIDatabaseScalability - DoorDashMediumSoftware EngineerDesign a Donation Service with Reliable Payment and Payout Tracking
Design donation collection and charity payouts with a PSP, idempotent state transitions, durable ledger records, asynchronous provider events, and reconciliation.
System DesignOnsite - DoorDashMediumSoftware EngineerDesign a Donation System for a Three-Day Fundraising Campaign
Design a donation system for a fundraising campaign that runs for exactly three days, where donors choose a charity, pay through a payment processor and see running totals. It tests payment idempotency and reconciliation, handling a time-boxed traffic burst, avoiding write hotspots on totals, and fraud protection.
System DesignOnsite
DoorDash