Airbnb interview questions

Showing 31–60 of 112 results

• Design a Stateful Working Hours RegisterHard

  Design an in-memory working hours and compensation tracking register that supports badge events, top-k leaderboards, scheduled rate changes, and interval-based historical earnings calculations.

  AirbnbSoftware EngineerSoftware Engineering FundamentalsOnline Assessment
• Design a banking ledger for deposits/withdrawalsMedium

  This question tests your ability to design a robust database schema and service logic for a banking system, focusing on data integrity, transaction atomicity, and handling high-concurrency balance updates.

  AirbnbSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Design a booking systemMedium

  This question tests the ability to design a distributed reservation system that handles high concurrency, prevents double-booking, and ensures data consistency at scale.

  AirbnbSoftware EngineerSystem DesignOnsite
• Design a dynamic rental pricing systemHard

  This question evaluates skills in production machine learning system design for pricing, including problem formulation, data and feature engineering, modeling and uncertainty management, online inference and scalability, experimentation and guardrails, and considerations like fairness and cold-start handling.

  AirbnbSoftware EngineerML System DesignOnsite
• Design a fast host listing metrics pageHard

  This question evaluates backend system design and data engineering competencies, including scalable API design, time-range aggregation correctness (handling partial overlaps and state changes), data modeling and indexing, caching and precomputation, and performance validation.

  AirbnbSoftware EngineerSystem DesignTechnical Screen
• Design a group chat systemHard

  Airbnb's onsite system design round asks you to design the backend for a real-time group chat and messaging system: 1:1 and group conversations, near-real-time delivery, accurate unread counts, and full paginated history at roughly 1B messages a day and 5M concurrent connections. A complete answer covers the guarantees, APIs, data model and partitioning, write path and ordering, WebSocket fan-out and presence, offline delivery and multi-device sync, unread counts, membership changes, failure modes and observability. This walkthrough gives a corrected end-to-end reference answer for every part, including the trade-offs interviewers probe.

  AirbnbSoftware EngineerSystem DesignOnsite
• Design a hot-listing waitlist APIHard

  Design a hot-listing waitlist API 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.

  AirbnbSoftware EngineerSystem DesignOnsite
• Design a multi-channel notification systemHard

  This question tests the ability to design a distributed, multi-channel notification system capable of handling high throughput, varying latency requirements across channels (e.g., email, push, SMS), and ensuring reliable message delivery.

  AirbnbSoftware EngineerSystem DesignTechnical Screen
• Design a network-aware Wi‑Fi badge experimentMedium

  This question evaluates a data scientist's proficiency in experimental design, causal inference under interference (including SUTVA risks), metric specification, power and sample‑size computation, analysis planning, and translating treatment effects into financial decision rules.

  AirbnbData ScientistAnalytics & ExperimentationTechnical Screen
• Design a real-time chat system with hot groupsHard

  This problem tests your ability to design a distributed, low-latency messaging system that handles massive fan-out and identify trending group activities.

  AirbnbSoftware EngineerSystem DesignOnsite
• Design a scalable consumer featureHard

  This question evaluates a candidate's ability to design large-scale recommendation systems, covering system architecture, real-time serving and offline pipelines, personalization and ML modeling (candidate generation and ranking), data modeling/feature stores, caching and storage, monitoring, experimentation, and privacy/compliance skills.

  AirbnbSoftware EngineerSystem DesignOnsite
• Design an A/B Testing PlatformHard

  Design an A/B testing platform with deterministic assignment, versioned experiment configuration, exposure logging, outcome attribution, and trustworthy analysis. Separate the latency-sensitive serving path from asynchronous metrics, support gradual ramps and overlapping tests, and detect bias, event loss, skew, and sample-ratio mismatch.

  AirbnbSoftware EngineerSystem DesignOnsite
• Design an A/B test with causal inferenceHard

  This question evaluates skills in experimental design, causal inference, and applied statistics — including estimand selection, sample-size calculation under clustering, integrity monitoring, handling noncompliance and contamination, sequential monitoring, and two-proportion inference — within the Analytics & Experimentation domain for a Data Scientist role. It is commonly asked because interviewers need to assess the ability to design and analyze robust A/B tests under real-world constraints; the prompt requires both conceptual understanding of causal assumptions and practical application of power calculations, diagnostics, and monitoring procedures.

  AirbnbData ScientistAnalytics & ExperimentationTechnical Screen
• Design an Airbnb wallet with holds and payoutsHard

  This question evaluates a candidate's competency in designing financial transaction systems, covering double-entry append-only ledgers, holds/authorizations and captures, refunds and payouts, multi-currency FX conversion and rounding, idempotency, concurrency safety, and auditable reconciliation.

  AirbnbSoftware EngineerSystem DesignTechnical Screen
• Design an In-Memory Cloud Storage Service with Users, Backups, and RestoreEasy

  Implement an in-memory cloud storage system supporting user storage limits, globally unique files, ranked file queries, account merges, and transactional backup and restore operations.

  AirbnbSoftware EngineerSoftware Engineering FundamentalsOnline Assessment
• Design an extensible request RetryerMedium

  This question evaluates a candidate's ability to design extensible and robust retry mechanisms, covering competencies in API/interface design, fault tolerance, backoff and jitter strategies, cancellation/deadline handling, idempotency considerations, and observability.

  AirbnbSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Design and Analyze Airbnb Locker ExperimentMedium

  This question evaluates a candidate's skills in experimental design and causal inference for marketplace features, including selecting the appropriate randomization unit, defining eligibility and treatment/control arms, and choosing primary, secondary, and guardrail metrics.

  AirbnbData ScientistAnalytics & ExperimentationTechnical Screen
• Design and assess an A/B testHard

  This problem tests your ability to design a statistically sound A/B test for a marketplace platform, including metric selection, power analysis considerations, and handling potential interference effects.

  AirbnbData ScientistAnalytics & ExperimentationOnsite
• Design and implement Connect Four engineMedium

  This question evaluates a candidate's competency in algorithmic problem solving, data structure selection, API design, complexity analysis, and testing through implementation of a Connect Four game engine.

  AirbnbSoftware EngineerCoding & AlgorithmsTechnical Screen
• Design and implement an Airbnb walletMedium

  This question evaluates system design and object-oriented design skills focused on transactional accounting, escrow-based payment flows, idempotency, and robust error handling, plus the ability to produce a runnable in-memory implementation.

  AirbnbSoftware EngineerSystem DesignTechnical Screen
• Design multi-currency pricing end-to-endHard

  This question evaluates understanding of multi-currency pricing and payments, covering currency selection UX, storage versus presentation currency, exchange-rate sourcing and locking, rounding and localization, tax and fee modeling, caching and cross-channel consistency, and API and data-model design in a distributed marketplace.

  AirbnbSoftware EngineerSystem DesignOnsite
• Design mutable sum-tree with fast queriesMedium

  This question evaluates proficiency in designing dynamic data structures for mutable rooted trees, including maintenance of subtree sums, parent/child link management, and analysis of update and query complexities within the Coding & Algorithms domain; it emphasizes practical application of algorithmic design coupled with conceptual understanding of invariants and amortized complexity. It is commonly asked in technical interviews because it probes reasoning about correctness and performance under mutations, handling edge cases such as subtree deletion and reattachment, and the ability to specify algorithmic approaches and complexity guarantees rather than implementation details.

  AirbnbSoftware EngineerCoding & AlgorithmsOnsite
• Design photo and listing quality modelsMedium

  This question tests the end-to-end design of a machine learning system to evaluate the quality of listing photos and overall listing attractiveness to improve search ranking and conversion.

  AirbnbMachine Learning EngineerMachine LearningOnsite
• Design rental watchlist and notification systemHard

  This question evaluates system architecture and scalability competencies, including data modeling for date-range watchlists, event-driven notification pipelines, time-zone and DST handling, consistency and concurrency semantics, idempotency, sharding/caching strategies, and privacy/analytics considerations.

  AirbnbSoftware EngineerSystem DesignOnsite
• Design robust primary and guardrail metricsHard

  This question evaluates proficiency in experiment metric design, guardrail definition, data quality diagnostics, and statistical analysis for A/B testing, including power calculations and sequential monitoring, within the Analytics & Experimentation domain.

  AirbnbData ScientistAnalytics & ExperimentationTechnical Screen
• Design scalable notification systemHard

  Airbnb's onsite system design round asks you to design a notification system that delivers email, SMS, and push messages to millions of guests, hosts, and employees, supporting both event-triggered sends and large batch campaigns. A complete answer covers requirements and scale math, architecture and data flow for both modes, the data model and API, templating, user preferences and compliance, prioritization, deduplication and idempotency, retries and failover, scaling and backpressure, observability, and cost. This walkthrough gives a corrected end-to-end reference answer for every part, including the trade-offs interviewers probe.

  AirbnbSoftware EngineerSystem DesignOnsite
• Detect overlap of two linked lists with cyclesHard

  This problem tests your ability to detect if two linked lists merge, specifically when they may contain cycles, by requiring logic to identify loop entry points and intersection nodes.

  AirbnbSoftware EngineerCoding & AlgorithmsOnsite
• Determine Exact Layover BookingMedium

  Determine if a subset of layover activities can be booked such that their total cost exactly matches a target voucher balance, handling floating-point currency without precision loss.

  AirbnbSoftware EngineerCoding & AlgorithmsTechnical Screen
• Discuss ML Project TradeoffsMedium

  This question evaluates a candidate's skills in model selection, trade-off analysis between precision, recall, latency and infrastructure cost, threshold tuning, reconciliation of offline versus online metrics, and comparative understanding of recommendation models within the Machine Learning domain.

  AirbnbMachine Learning EngineerMachine LearningOnsite
• Discuss learning and feedback experiencesMedium

  This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Discuss learning and feedback experiences states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  AirbnbSoftware EngineerBehavioral & LeadershipTechnical Screen