Google interview questions

Showing 151–180 of 486 results

• Design a real-time recommendation systemHard

  This question evaluates a candidate's competency in designing large-scale, low-latency real-time recommendation systems, covering feature engineering and feature-store consistency, candidate generation and ranking architectures, cold-start handling, latency versus accuracy trade-offs, monitoring, and operational scalability.

  GoogleMachine Learning EngineerML System DesignOnsite
• Design a rolling hit counter APIMedium

  This question tests the ability to design an efficient data structure for time-series aggregation using a sliding window approach with O(1) time complexity per operation.

  GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
• Design a scalable video platform databaseMedium

  This question evaluates relational database design and data engineering competencies—including schema modeling, many-to-many relationships, idempotent ingest, indexing and partitioning, OLTP versus analytics integration, GDPR-compliant deletion strategies, and query formulation—within the Data Manipulation (SQL/Python) domain for a Data Scientist role. It is commonly asked to assess both conceptual understanding and practical application of scalable data architectures, performance tuning, and compliance trade-offs, focusing on the ability to reason about schema choices, read/write optimization, and analytics integration without implementation details.

  GoogleData ScientistData Manipulation (SQL/Python)Technical Screen
• Design a waitlist managerEasy

  This question tests your ability to design a waitlist system using efficient data structures to handle insertions, removals, and lookup operations.

  GoogleSoftware EngineerSoftware Engineering FundamentalsOnsite
• Design a waitlist system with top/bottom KMedium

  This problem tests your ability to design a dynamic waitlist using efficient data structures to support logarithmic time complexity for insertions, deletions, and ranking operations.

  GoogleSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Design a watch-next video recommender and derive its losses and optimizer update rulesMedium

  Design the watch-next recommendations shown while a user watches a video, from objectives and candidate generation to ranking, serving and evaluation. The interview probes modeling depth: exact loss functions for retrieval and multi-task ranking, the gradient at the output logit, and the update rules of the optimizers used to train each model.

  GoogleMachine Learning EngineerML System DesignOnsite
• Design an A/B test for search rankingEasy

  This question tests the ability to design a statistically sound A/B test for a search ranking algorithm, focusing on metric selection, hypothesis formulation, and common pitfalls in experimentation.

  GoogleData ScientistAnalytics & ExperimentationHR Screen
• Design an Agent for Internal Document SearchMedium

  Design an enterprise search agent that provides grounded, cited answers over internal knowledge repositories while strictly enforcing access control lists (ACLs) and handling prompt injection.

  GoogleSoftware EngineerML System DesignTechnical Screen
• Design an Embeddable Streaming Chat InterfaceHard

  Design an embeddable chat-agent widget with resumable streaming, virtualized history, safe caching, accessibility, and meaningful metrics.

  GoogleFrontend EngineerSystem DesignOnsite
• Design an Employee Coverage TimelineMedium

  This problem tests your ability to handle overlapping intervals and state tracking using a sweep-line algorithm combined with a mapping structure.

  GoogleSoftware EngineerSoftware Engineering FundamentalsOnsite
• Design an Enterprise AI Adoption Agent for a Global CompanyMedium

  Prepare for a Google system design interview about design an enterprise ai adoption agent for a global company. This question focuses on requirements, architecture, trade-offs, reliability, and follow-up discussion areas.

  GoogleSoftware EngineerSystem DesignOnsite
• Design an LLM Agent for Manufacturing: Production Status, Work Orders and QuotesMedium

  Design an LLM-powered agent for a manufacturing business that checks production progress, opens work orders and gives customers price quotes. Probes tool design for reads and writes, how to stop the agent from inventing statuses or prices, and how to enforce user permissions outside the model.

  GoogleSoftware EngineerML System DesignTechnical Screen
• Design an Offline-First Client That Syncs Edits and Resolves Multi-Device ConflictsMedium

  Design the client side of an app where users keep editing data offline, store every edit locally, and sync with the server when the network returns. Covers the local data model and edit queue, a sync protocol that is safe to retry, and detecting and resolving version conflicts when several devices change the same data.

  GoogleSoftware EngineerSystem DesignOnsite
• Design an Online Coding Judge PlatformMedium

  This question tests the ability to design a high-throughput, secure, and fault-tolerant distributed system capable of executing untrusted user code in isolated environments.

  GoogleSoftware EngineerSystem DesignOnsite
• Design an Unbiased Upgrade ExperimentHard

  This question tests the ability to design an A/B test for a software upgrade, specifically focusing on handling non-compliance, selection bias, and the identification of causal effects in a real-world product environment.

  GoogleData ScientistAnalytics & ExperimentationTechnical Screen
• Design an ads retrieval service using a heapEasy

  This question tests the ability to design a retrieval system using a priority queue and the implementation of efficient operations to maintain a sorted collection of ad candidates.

  GoogleSoftware EngineerSoftware Engineering FundamentalsOnsite
• Design an editable sequence with markerMedium

  This question evaluates understanding of mutable ordered sequence data structures, marker semantics and invariants, API and data model design, and algorithmic time-complexity trade-offs for insert, delete, and move operations.

  GoogleSoftware EngineerSoftware Engineering FundamentalsOnsite
• Design an elevator control systemHard

  This question evaluates system design skills including architectural modeling of components, scheduling and concurrency control, state-machine design, and fault-tolerance for real-time control systems, and falls under the System Design domain.

  GoogleSoftware EngineerSystem DesignOnsite
• Design anomaly detection and response platformHard

  This question evaluates a candidate's competency in designing end-to-end ML-driven systems that handle large-scale, low-latency OS snapshot ingestion, binary anomaly detection, decisioning and action orchestration with multi-tenant security, auditability, and failure rollback.

  GoogleSoftware EngineerML System DesignTechnical Screen
• Design at-least-once notification deliveryMedium

  This question evaluates expertise in reliable distributed systems design, including at-least-once delivery semantics, idempotency and deduplication strategies, retry and dead-letter handling, API and message-schema design, ordering and out-of-order handling, and scalability for high-throughput multi-tenant notification platforms.

  GoogleSoftware EngineerSystem DesignTechnical Screen
• Design compressed vector and compute dot productEasy

  This problem tests your ability to design a memory-efficient data structure for sparse or repetitive vector data and implement an arithmetic operation without fully decompressing the representation.

  GoogleSoftware EngineerCoding & AlgorithmsOnsite
• Design deduplicated file storage on filesystemHard

  This question evaluates system design and storage engineering competencies, including multi-tenant isolation, authentication and authorization models, content-addressable storage and deduplication, reference counting and garbage collection, concurrency control, API surface design, and scaling across nodes using only filesystem primitives.

  GoogleSoftware EngineerSystem DesignTechnical Screen
• Design distributed log storage serviceHard

  This question evaluates a candidate's expertise in designing distributed storage systems, covering partitioned append-only logs, high-throughput writes and reads, replication, retention, indexing, compaction, leader/follower roles, and recovery mechanisms.

  GoogleSoftware EngineerSystem DesignTechnical Screen
• Design distributed transactions protocolHard

  This question evaluates a candidate's understanding of distributed transactions, coordination protocols, fault tolerance, consistency, and reliability across microservices and databases.

  GoogleSoftware EngineerSystem DesignTechnical Screen
• Design executable notebook service APIsHard

  This question evaluates a candidate's competence in designing secure, scalable systems for executing user-supplied code, covering API design, sandboxing and isolation, dependency management, resource limits, scheduling, and streaming proxies for logs/results.

  GoogleSoftware EngineerSystem DesignTechnical Screen
• Design feedback-driven recommenderHard

  Design feedback-driven recommender evaluates ML product requirements, data/labeling, modeling, serving architecture, evaluation, monitoring, and trade-offs in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  GoogleMachine Learning EngineerML System DesignOnsite
• Design high-throughput event subscription systemHard

  This question evaluates a candidate's ability to design scalable, fault-tolerant event ingestion and subscription architectures, covering distributed systems, high-throughput messaging, content-based filtering, multi-tenant isolation, API/webhook design, delivery semantics, backpressure, sharding, security, and operational observability.

  GoogleSoftware EngineerSystem DesignTechnical Screen
• Design human review to estimate model accuracyHard

  This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Design human review to estimate model accuracy states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  GoogleData ScientistStatistics & MathOnsite
• Design key management serviceHard

  This question evaluates system design and security competencies—specifically cryptographic key lifecycle management, HSM integration, access control, auditing, multi-tenant isolation, and scalability—within the System Design domain.

  GoogleSoftware EngineerSystem DesignTechnical Screen
• Design large-scale near-duplicate video detectionHard

  This question tests the ability to design an end-to-end pipeline for detecting near-duplicate videos at a massive scale, focusing on embedding generation, vector indexing, and trade-offs between precision and recall.

  GoogleMachine Learning EngineerSystem DesignOnsite