LinkedIn interview questions

Showing 31–60 of 154 results

• Design Top K ranking systemHard

  Design Top K ranking system 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.

  LinkedInSoftware EngineerSystem DesignOnsite
• Design a CI Job Scheduler with Live Build OutputMedium

  Design a scalable continuous integration (CI) platform that schedules dependency-aware build jobs across worker fleets and streams live console output to end users.

  LinkedInDevOps EngineerSystem DesignOnsite
• Design a CI/CD Task SchedulerMedium

  Design the core distributed task scheduling engine for an enterprise CI/CD platform that coordinates DAG-based workflows across heterogeneous worker pools.

  LinkedInSoftware EngineerSystem DesignOnsite
• Design a Calendar SystemMedium

  Tests your ability to design a scalable calendar backend that supports single and recurring events, attendee invitations, and time-based reminder notifications with timezone awareness.

  LinkedInSoftware EngineerSystem DesignTechnical Screen
• Design a Distributed Key-Value Store for a Small Company's Internal UseMedium

  Design a distributed key-value store for internal use at a small company. The question tests comparing centralized, decentralized and hybrid architectures, and depth on partitioning, rebalancing, replication, failure handling, consistency, hot keys and availability at a senior infrastructure level.

  LinkedInSoftware EngineerSystem DesignOnsite
• Design a Global Calendar ServiceMedium

  This question evaluates competence in designing scalable, time-zone aware calendaring systems, covering API and data model design, recurrence representation, daylight saving semantics, conflict detection, storage strategy, and consistency trade-offs.

  LinkedInSoftware EngineerSystem DesignOnsite
• Design a Model That Predicts Whether a Member Clicks a Displayed JobHard

  An ML system design question: predict whether a member will click a job displayed to them, using member features, job content and interaction history. It tests defining the supervision signal and training data, choosing a loss, preventing data leakage, building member and job embeddings, and laying out the training and serving components.

  LinkedInMachine Learning EngineerML System DesignTechnical Screen
• Design a Multi-Region Malicious-IP Detection SystemHard

  Design a globally distributed, low-latency edge security service that detects and blocks malicious IP addresses across regions, featuring decentralized evaluation, asynchronous intelligence sharing, and rapid false-positive rollback.

  LinkedInSoftware EngineerSystem DesignTechnical Screen
• Design a Personalized Feed and Compare Ranking ObjectivesMedium

  Design an end-to-end personalized professional feed system and compare pointwise, pairwise, and listwise learning-to-rank formulations across offline training, online serving, and business metrics.

  LinkedInMachine Learning EngineerML System DesignTechnical Screen
• Design a Personalized Job Suggestions Page for LinkedIn MembersMedium

  Design the LinkedIn page that suggests open jobs to a signed-in member, from candidate retrieval and filtering to ranking, pagination and serving. Tests large-scale recommendation architecture, freshness for new and closed postings, feedback logging, latency budgets and graceful degradation.

  LinkedInSoftware EngineerSystem DesignOnsite
• Design a Raffle Drum That Draws Duplicate Tickets Fairly in O(1)Medium

  Design a drum that holds raffle ticket codes, where the same code can be dropped in more than once, and supports adding a ticket, pulling a specific ticket out, and drawing one at random so every physical ticket in the drum is equally likely to come out — all in average O(1) time. Tests combining an array with a hash index so removal and random draw both stay constant time even with string keys and duplicates.

  LinkedInSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Design a Randomized MultisetMedium

  This question evaluates the ability to design and implement a randomized multiset that correctly handles duplicate integer occurrences while providing expected O(1) insert, remove, and uniform getRandom operations, testing knowledge of data structures, randomness, and performance constraints.

  LinkedInSoftware EngineerCoding & AlgorithmsTechnical Screen
• Design a Ranked Social Feed with Hybrid Fan-OutMedium

  Design a scalable, read-heavy ranked social feed supporting millions of users. The system must balance fan-out-on-write and fan-out-on-read while ensuring read-your-own-writes consistency for authors.

  LinkedInSoftware EngineerSystem DesignOnsite
• Design a Scalable Calendar ServiceMedium

  Design calendar event storage and time-range reads, explain concurrent edits and scaling, and clarify recurrence and notification requirements.

  LinkedInSoftware EngineerSystem DesignOnsite
• Design a Scalable Error Message Counting ServiceMedium

  Design a service that receives application error messages and reports how often each distinct error occurs over time. It tests grouping varied messages into error signatures, absorbing bursty write traffic during incidents, time-windowed aggregation, top-error queries and count accuracy under failures.

  LinkedInSoftware EngineerSystem DesignOnsite
• Design a Skills inference systemMedium

  This question assesses the ability to build an end-to-end ML pipeline for extracting and normalizing professional skills from unstructured user-generated text, such as job descriptions or member profiles.

  LinkedInMachine Learning EngineerML System DesignOnsite
• Design a Top-K Ranking ServiceEasy

  This question tests the ability to design a distributed, low-latency system capable of maintaining and serving a real-time 'Top-K' list of items (e.g., trending hashtags) across a massive stream of incoming data.

  LinkedInSoftware EngineerSystem DesignOnsite
• Design a Top-K search words serviceMedium

  The question evaluates understanding of scalable, low-latency analytics and search-event systems, including high-throughput event ingestion, Top-K aggregation across all-time and sliding windows, normalization/deduplication trade-offs, and multi-region consistency considerations.

  LinkedInSoftware EngineerSystem DesignTechnical Screen
• Design a company-wide monitoring systemMedium

  This question evaluates skills in designing large-scale observability and monitoring systems, covering telemetry collection (metrics, logs, traces), high-throughput ingestion, storage and scaling strategies, alerting pipelines, and operational trade-offs like cardinality, retention, and backpressure.

  LinkedInSoftware EngineerSystem DesignOnsite
• Design a distributed key-value storeHard

  Design a distributed key-value store 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.

  LinkedInMachine Learning EngineerSystem DesignTechnical Screen
• Design a malicious-URL checking service using an isMalicious APIMedium

  This question tests your ability to design a high-throughput, low-latency URL reputation checking service, focusing on caching strategies, scalability, and system resilience.

  LinkedInSoftware EngineerSystem DesignOnsite
• Design a max-stack with efficient operationsMedium

  This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Design a max-stack with efficient operations states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  LinkedInSoftware EngineerCoding & AlgorithmsOnsite
• Design a meeting scheduler APIMedium

  This problem tests your ability to design a thread-safe scheduling system using interval management techniques and efficient data structures for range querying.

  LinkedInSoftware EngineerSoftware Engineering FundamentalsOnsite
• Design a metrics platform without alertingMedium

  This problem tests your ability to design a high-throughput time-series metrics system, focusing on ingestion pipelines, efficient storage schema for multi-dimensional data, and query performance.

  LinkedInSoftware EngineerSystem DesignOnsite
• Design a scalable calendar systemHard

  This question evaluates a candidate's ability to design a scalable, multi-tenant calendar platform, testing competencies in distributed systems architecture, API and data-model design for events/recurrence/time zones, access control and privacy boundaries, notification pipelines, and external integration.

  LinkedInSoftware EngineerSystem DesignOnsite
• Design a scalable key-value storeMedium

  This system design question evaluates expertise in distributed systems and scalable storage architecture within the System Design domain, focusing on data partitioning, replication, durability, consistency models, and low-latency operation.

  LinkedInSoftware EngineerSystem DesignOnsite
• Design a short-video recommender systemEasy

  This question assesses the ability to architect a multi-stage machine learning pipeline for a short-video feed, covering candidate generation, ranking, and performance evaluation.

  LinkedInData ScientistMachine LearningTechnical Screen
• Design a stack with max removalMedium

  This question evaluates data-structure design and algorithmic complexity analysis by requiring a stack-like structure that supports standard stack operations plus efficient maximum retrieval and targeted removal, assessing practical implementation skills and time-complexity reasoning at a practical application level.

  LinkedInSoftware EngineerCoding & AlgorithmsTechnical Screen
• Design a system for LinkedIn SkillsMedium

  This question evaluates a machine learning engineer's ability to design an end-to-end ML system for skill inference and recommendation on a professional networking platform, testing competencies in data sourcing and labeling, feature engineering, model selection (including LLM integration), online serving, monitoring, and quality control.

  LinkedInMachine Learning EngineerML System DesignOnsite
• Design an ML Forecasting and Pacing System for Ad BiddingMedium

  Design an ad forecasting and budget pacing architecture that combines predictive ML with deterministic budget guardrails to optimize campaign delivery across non-stationary traffic.

  LinkedInMachine Learning EngineerML System DesignTechnical Screen