# LinkedIn Interview Guide 2026: Social Graph Engineering, Feed Ranking, and Professional Network Scale

Source: https://www.techinterview.org/post/3233460278/linkedin-interview-guide-2026-social-graph-engineering-feed-ranking-and-professional-network-scale/
Updated: 2026-07-05 · techinterview.org

## LinkedIn Interview Guide 2026: Social Graph Engineering, Data Systems, and Professional Network Scale

LinkedIn operates the world's largest professional network with 1B+ members. Their engineering challenges center on social graph queries at scale, feed ranking, job matching ML, and real-time notifications. This guide covers SWE interviews from Staff E4 through Staff E6.

## The LinkedIn Interview Process

- **Recruiter screen** (30 min)

- **Technical phone screen** (1 hour) — 1–2 coding problems

- **Onsite** (4–5 rounds):

  2× coding (LeetCode-style, medium-hard)

  - 1× system design (feed, search, messaging, or graph)

  - 1× hiring manager / values alignment

  - 1× (for senior) cross-functional leadership discussion

LinkedIn acquired by Microsoft in 2016; culture blends LinkedIn's original startup DNA with Microsoft's enterprise rigor. Expect questions about impact measurement and data-driven decisions.

## Core Algorithms: Graph Problems

LinkedIn's core data structure is the social graph. Expect graph traversal, shortest paths, and degree-of-separation queries.

### Second-Degree Connection Discovery


```
from collections import defaultdict, deque
from typing import Set, Dict, List

class ProfessionalGraph:
    """
    Social graph operations used in LinkedIn's "People You May Know" feature.
    LinkedIn's actual graph has 1B+ nodes; uses distributed graph databases
    (Voldemort, Espresso) with sharding by member ID.
    """

    def __init__(self):
        self.adjacency = defaultdict(set)  # member_id -> set of connection_ids

    def add_connection(self, a: int, b: int):
        self.adjacency[a].add(b)
        self.adjacency[b].add(a)

    def get_connections(self, member_id: int, degree: int) -> Dict[int, int]:
        """
        BFS to find all connections within `degree` hops.
        Returns {member_id: distance} dict.

        Time: O(V + E) in the local neighborhood
        Space: O(V) visited set
        """
        visited = {member_id: 0}
        queue = deque([member_id])

        while queue:
            current = queue.popleft()
            current_dist = visited[current]

            if current_dist >= degree:
                continue

            for neighbor in self.adjacency[current]:
                if neighbor not in visited:
                    visited[neighbor] = current_dist + 1
                    queue.append(neighbor)

        visited.pop(member_id)  # exclude self
        return visited

    def people_you_may_know(
        self,
        member_id: int,
        limit: int = 20
    ) -> List[tuple]:
        """
        Suggest connections based on mutual connections count.

        Algorithm:
        1. Get all 2nd-degree connections (friends-of-friends not yet connected)
        2. Score by mutual connection count
        3. Return top-K by score

        Time: O(D1 * D2) where D1, D2 are avg degrees of 1st/2nd degree nodes
        """
        direct = self.adjacency[member_id]
        mutual_counts = defaultdict(int)

        for friend in direct:
            for friend_of_friend in self.adjacency[friend]:
                if friend_of_friend != member_id and friend_of_friend not in direct:
                    mutual_counts[friend_of_friend] += 1

        suggestions = [(count, person)
                       for person, count in mutual_counts.items()]
        suggestions.sort(reverse=True)
        return [(person, count) for count, person in suggestions[:limit]]

    def shortest_path(self, source: int, target: int) -> List[int]:
        """
        BFS shortest path between two members.
        LinkedIn's "How You're Connected" feature.

        Time: O(V + E)
        Space: O(V)
        """
        if source == target:
            return [source]

        parent = {source: None}
        queue = deque([source])

        while queue:
            current = queue.popleft()
            for neighbor in self.adjacency[current]:
                if neighbor not in parent:
                    parent[neighbor] = current
                    if neighbor == target:
                        # Reconstruct path
                        path = []
                        node = target
                        while node is not None:
                            path.append(node)
                            node = parent[node]
                        return path[::-1]
                    queue.append(neighbor)

        return []  # no path
```


### Job Recommendation with Skill Matching


```
class JobMatcher:
    """
    Simplified job recommendation using TF-IDF skill matching.
    LinkedIn's actual system uses Graph Neural Networks and
    feature-rich ML models with 100s of signals.

    Key signals: skill overlap, title match, location, seniority,
    company size preference, salary range, commute distance.
    """

    def __init__(self):
        self.jobs = {}  # job_id -> {required_skills, title, level, salary}

    def add_job(self, job_id: int, required_skills: List[str],
                title: str, level: str, min_salary: int):
        self.jobs[job_id] = {
            'skills': set(s.lower() for s in required_skills),
            'title': title.lower(),
            'level': level,
            'min_salary': min_salary,
        }

    def score_match(
        self,
        member_skills: List[str],
        desired_salary: int,
        desired_level: str,
        job_id: int
    ) -> float:
        """
        Score how well a job matches a member's profile.
        Returns score in [0, 1].
        """
        job = self.jobs[job_id]
        member_skill_set = set(s.lower() for s in member_skills)

        # Skill overlap (Jaccard similarity)
        intersection = member_skill_set & job['skills']
        union = member_skill_set | job['skills']
        skill_score = len(intersection) / len(union) if union else 0

        # Level match
        level_score = 1.0 if job['level'] == desired_level else 0.5

        # Salary fit
        if job['min_salary'] <= desired_salary * 1.1:
            salary_score = 1.0
        elif job['min_salary'] <= desired_salary * 1.3:
            salary_score = 0.6
        else:
            salary_score = 0.2

        # Weighted combination of signals
        return (
            0.5 * skill_score +
            0.3 * level_score +
            0.2 * salary_score
        )

    def recommend(
        self,
        member_skills: List[str],
        desired_salary: int,
        desired_level: str,
        limit: int = 10
    ) -> List[tuple]:
        scores = [
            (self.score_match(member_skills, desired_salary, desired_level, jid), jid)
            for jid in self.jobs
        ]
        scores.sort(reverse=True)
        return [(jid, score) for score, jid in scores[:limit]]
```


## System Design: LinkedIn Feed

Common question: *"Design LinkedIn's news feed."*

### Fan-Out Strategies


```
"""
LinkedIn Feed Architecture:

Two approaches to fan-out:

1. Fan-out on Write (Push model):
   - When Alice posts, immediately write to all her followers' feeds
   - Pro: Fast reads (pre-computed)
   - Con: Expensive for members with 10K+ connections (celebrities)

2. Fan-out on Read (Pull model):
   - When Bob opens feed, pull recent posts from all connections
   - Pro: No wasted write work for inactive users
   - Con: Slow read, O(connections * posts_per_person)

LinkedIn uses HYBRID:
- Regular users ( float:
        """
        Multi-factor post scoring for feed ranking.
        post: {engagement_rate, author_connection_degree,
               topics, posted_at, sponsored}
        """
        import math

        # 1. Recency score (exponential decay)
        hours_old = (current_time - post['posted_at']) / 3600
        recency = math.exp(-hours_old / self.recency_half_life_hours)

        # 2. Engagement score (predicted based on similar posts)
        engagement = post.get('predicted_engagement_rate', 0.05)

        # 3. Social proximity (1st degree > 2nd degree > 3rd degree)
        proximity_weights = {1: 1.0, 2: 0.6, 3: 0.3, 0: 0.2}
        proximity = proximity_weights.get(post.get('author_connection_degree', 0), 0.1)

        # 4. Topic relevance
        viewer_topics = set(viewer_profile.get('interests', []))
        post_topics = set(post.get('topics', []))
        topic_overlap = len(viewer_topics & post_topics) / max(len(viewer_topics | post_topics), 1)

        # 5. Sponsored content gets score cap
        if post.get('sponsored'):
            return min(0.3, 0.15 * recency + 0.1 * engagement)

        return (0.35 * recency + 0.30 * engagement +
                0.20 * proximity + 0.15 * topic_overlap)
```


## LinkedIn-Specific Technical Topics

- **Voldemort**: LinkedIn's distributed key-value store (open source); used for member profiles, connections

- **Kafka**: Open-sourced by LinkedIn; used for activity streams, notifications, audit logs

- **Espresso**: Document store for mutable data with ACID transactions

- **Pinot**: Real-time analytics at LinkedIn (who viewed your profile counts)

- **Venice**: Derived data store fed by Kafka for fast read serving

## Behavioral Questions at LinkedIn

- **"How have you created economic opportunity for others?"** — LinkedIn's mission; connect your work to job market impact

- **Ownership and initiative**: Examples of driving projects without being asked

- **Data-driven decision making**: How you've used metrics to guide engineering decisions

- **Collaboration across orgs**: LinkedIn has many teams; cross-functional work matters

## Compensation (E4–E6, US, 2025 data)

| Level | Title | Base | Total Comp |
| --- | --- | --- | --- |
| E4 | SWE | $180–210K | $250–330K |
| E5 | Senior SWE | $210–250K | $340–450K |
| E6 | Staff SWE | $250–300K | $460–620K |

LinkedIn (Microsoft subsidiary) RSUs are in Microsoft stock, which provides stability. Vest quarterly over 4 years.

## Interview Tips

- **Use LinkedIn**: Understand the feed, search, InMail, job recommendations as a power user

- **Graph algorithms**: BFS/DFS, Dijkstra, topological sort — all relevant to social graph problems

- **Read LinkedIn Engineering Blog**: engineering.linkedin.com has deep posts on their systems

- **Know Kafka deeply**: LinkedIn invented it; knowing producer/consumer groups, partition design is a plus

- **SQL and analytics**: LinkedIn uses heavy analytics; complex window functions, CTEs are fair game

*Practice problems: LeetCode 133 (Clone Graph), 684 (Redundant Connection), 1334 (Find the City), 547 (Number of Provinces).*

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- [Topological Sort Interview Patterns: Kahn's Algorithm, DFS Ordering, Cycle Detection](https://techinterview.org/topological-sort-interview-patterns/)

- [System Design: Collaborative Document Editing (Google Docs)](https://techinterview.org/system-design-collaborative-editing/)

- [Matrix and Grid DP Interview Patterns: Unique Paths, Minimum Path Sum, Dungeon](https://techinterview.org/matrix-grid-dp-interview-patterns/)

- [System Design: Real-Time Analytics Dashboard (ClickHouse / Druid)](https://techinterview.org/system-design-real-time-analytics/)

- [Segment Tree and Fenwick Tree (BIT) Interview Patterns](https://techinterview.org/segment-tree-fenwick-tree-patterns/)

- [System Design: Distributed Job Scheduler (Cron at Scale)](https://techinterview.org/system-design-job-scheduler/)

- [Recursion Interview Patterns: Memoization, Tree Recursion, Classic Problems](https://techinterview.org/recursion-interview-patterns/)

- [Bit Manipulation Interview Patterns: XOR Tricks, Bit Masks, Power of 2](https://techinterview.org/bit-manipulation-interview-patterns/)

- [Divide and Conquer Interview Patterns: Merge Sort, Quick Select, Master Theorem](https://techinterview.org/divide-and-conquer-interview-patterns/)

- [Monotonic Stack Interview Patterns: Next Greater, Histograms, Stock Span](https://techinterview.org/monotonic-stack-interview-patterns/)

- [System Design: Distributed Message Queue (Kafka / SQS)](https://techinterview.org/system-design-message-queue/)

- [Union-Find (Disjoint Set Union) Interview Patterns](https://techinterview.org/union-find-interview-patterns/)

- [Backtracking Interview Patterns: Subsets, Permutations, N-Queens](https://techinterview.org/backtracking-interview-patterns/)

- [Binary Tree Interview Patterns: Traversal, DFS, BFS, and Classic Problems](https://techinterview.org/binary-tree-interview-patterns/)

- [System Design: Real-Time Chat System (WhatsApp / Slack)](https://techinterview.org/system-design-chat-system/)

- [System Design: File Storage and Sync Service (Dropbox)](https://techinterview.org/system-design-file-storage-sync/)

- [String DP Interview Patterns: LCS, Edit Distance, Palindrome DP](https://techinterview.org/string-dp-interview-patterns/)

- [Linked List Interview Patterns](https://techinterview.org/linked-list-interview-patterns/)

- [System Design: Twitter / Social Media Feed Architecture](https://techinterview.org/system-design-twitter-social-media-feed/)

- [System Design: Video Streaming Platform (Netflix/YouTube)](https://techinterview.org/system-design-video-streaming-platform/)

- [Dynamic Programming Knapsack Patterns](https://techinterview.org/dynamic-programming-knapsack-patterns/)

- [System Design: URL Shortener (bit.ly/TinyURL)](https://techinterview.org/system-design-url-shortener/)

- [System Design: Email Service at Scale (SendGrid/Gmail)](https://techinterview.org/system-design-email-service/)

- [Interval and Greedy Algorithm Interview Patterns](https://techinterview.org/interval-greedy-interview-patterns/)

- [System Design: Autocomplete and Typeahead Service](https://techinterview.org/system-design-autocomplete-typeahead/)

- [System Design: Machine Learning Platform and MLOps](https://techinterview.org/system-design-ml-platform-mlops/)

- [Stack and Queue Interview Patterns](https://techinterview.org/stack-queue-interview-patterns/)

- [System Design: API Gateway and Service Mesh](https://techinterview.org/system-design-api-gateway-service-mesh/)

- [Binary Search Interview Patterns](https://techinterview.org/binary-search-interview-patterns/)

- [System Design: Multi-Tenant SaaS Architecture](https://techinterview.org/system-design-multi-tenant-saas/)

- [Sliding Window and Two Pointer Interview Patterns](https://techinterview.org/sliding-window-two-pointer-patterns/)

- [System Design: Kubernetes and Container Orchestration](https://techinterview.org/system-design-kubernetes-container-orchestration/)

- [System Design: Event Sourcing and CQRS](https://techinterview.org/system-design-event-sourcing-cqrs/)

- [Graph Algorithm Interview Patterns](https://techinterview.org/graph-interview-patterns/)

- [Trie and String Algorithm Interview Patterns](https://techinterview.org/trie-string-interview-patterns/)

- [System Design: Recommendation Engine at Scale](https://techinterview.org/system-design-recommendation-engine/)

## Related System Design Topics

- [Heap and Priority Queue Interview Patterns](https://techinterview.org/heap-priority-queue-patterns/)

📌 Related System Design: [Low-Level Design: Chess Game (OOP Interview)](https://techinterview.org/lld-chess-game/)

📌 Related System Design: [Database Sharding: Complete System Design Guide](https://techinterview.org/database-sharding-system-design/)

📌 Related: [System Design Interview: Design Instagram / Photo Sharing Platform](https://techinterview.org/system-design-instagram-photo-sharing/)

📌 Related: [System Design Interview: Design WhatsApp / Real-Time Messaging](https://techinterview.org/system-design-whatsapp-messaging/)

📌 Related: [System Design Interview: Design an E-Commerce Platform (Amazon-Scale)](https://techinterview.org/system-design-ecommerce-platform/)

📌 Related: [System Design Interview: Design Twitter / X Timeline](https://techinterview.org/system-design-twitter-timeline/)

📌 Related: [Graph Traversal Interview Patterns (2025)](https://techinterview.org/graph-traversal-interview-patterns/)

📌 Related: [Low-Level Design: Chat Application (OOP Interview)](https://techinterview.org/lld-chat-application/)

📌 Related: [System Design Interview: Design a Social Media News Feed](https://techinterview.org/system-design-news-feed/)

📌 Related: [System Design Interview: Design a Distributed Message Queue (Kafka)](https://techinterview.org/system-design-message-queue-kafka/)

📌 Related: [Low-Level Design: Pub/Sub Event System (OOP Interview)](https://techinterview.org/lld-pub-sub-event-system/)

📌 Related: [Low-Level Design: Task Scheduler / Job Queue (OOP Interview)](https://techinterview.org/lld-task-scheduler-job-queue/)

📌 Related: [System Design Interview: Design a Distributed Search Engine](https://techinterview.org/system-design-distributed-search/)

📌 Related: [Low-Level Design: Notification System (OOP Interview)](https://techinterview.org/lld-notification-system/)

📌 Related: [Low-Level Design: Logging Framework (OOP Interview)](https://techinterview.org/lld-logging-framework/)

📌 Related: [Low-Level Design: Library Management System (OOP Interview)](https://techinterview.org/lld-library-management-system/)

📌 Related: [System Design Interview: Design a Search Autocomplete (Typeahead)](https://techinterview.org/system-design-autocomplete/)

📌 Related: [Low-Level Design: Online Auction System (OOP Interview)](https://techinterview.org/lld-online-auction-system/)

📌 Related: [Low-Level Design: Stock Order Book (Trading System OOP Interview)](https://techinterview.org/lld-stock-order-book/)

📌 Related: [Low-Level Design: Social Network Friend Graph (OOP Interview)](https://techinterview.org/lld-social-network/)

Related system design: [Low-Level Design: Vending Machine (State Pattern OOP Interview)](https://techinterview.org/lld-vending-machine/)

Related system design: [Low-Level Design: Elevator System (SCAN, Dispatch, State Machine)](https://techinterview.org/lld-elevator-system/)

Related system design: [Union-Find (DSU) Interview Patterns: Connected Components, MST, Kruskal](https://techinterview.org/union-find-dsu-interview-patterns/)

 Related: [System Design: Feature Flag and A/B Testing System](https://techinterview.org/system-design-feature-flags/)

Related system design: [Sliding Window Interview Patterns: Fixed, Variable, Deque (2025)](https://techinterview.org/sliding-window-interview-patterns/)

Related system design: [Two Pointers Interview Patterns: Two Sum, 3Sum, Cycle Detection (2025)](https://techinterview.org/two-pointers-interview-patterns/)

Related system design: [Dynamic Programming Interview Patterns: Knapsack, LCS, Interval DP (2025)](https://techinterview.org/dynamic-programming-interview-patterns/)

Related system design: [Low-Level Design: Social Media Feed (Follow, Post, Fan-out, Likes)](https://techinterview.org/lld-social-media-feed/)

Related system design: [Stack Interview Patterns: Monotonic Stack, Calculator, Min Stack (2025)](https://techinterview.org/stack-interview-patterns/)

Related system design: [System Design: Apache Kafka — Architecture, Partitions, and Stream Processing](https://techinterview.org/system-design-kafka-architecture/)

Related system design: [System Design: Collaborative Document Editing (Google Docs) — OT, CRDT, and WebSockets](https://techinterview.org/system-design-collaborative-document-editing/)

Related system design: [System Design: Distributed Counters, Leaderboards, and Real-Time Analytics](https://techinterview.org/system-design-distributed-counters-analytics/)

Related system design: [System Design: Real-time Chat and Messaging System (WhatsApp/Slack) — WebSockets, Pub/Sub, Scale](https://techinterview.org/system-design-real-time-chat/)

Related system design: [Matrix Interview Patterns: BFS/DFS on Grids, Island Count, Shortest Path (2025)](https://techinterview.org/matrix-interview-patterns/)

Related system design: [Sorting Algorithms Interview Patterns: Merge Sort, Quick Sort, Heap Sort, Counting Sort (2025)](https://techinterview.org/sorting-algorithms-interview-patterns/)

Related system design: [Trie Interview Patterns: Autocomplete, Word Search, Prefix Matching (2025)](https://techinterview.org/trie-interview-patterns/)

Related system design: [Low-Level Design: Social Media Post Scheduler -- Scheduling, Multi-Platform Publishing, and Analytics](https://techinterview.org/lld-social-media-post-scheduler/)

Related system design: [String Sliding Window Interview Patterns: Longest Substring, Anagram, Minimum Window (2025)](https://techinterview.org/string-sliding-window-interview-patterns/)

Related system design: [2D Dynamic Programming Interview Patterns: LCS, Edit Distance, Knapsack, Grid Paths (2025)](https://techinterview.org/two-dimensional-dp-interview-patterns/)

Related system design: [Low-Level Design: Employee Leave Management System — Accrual, Approval Workflows, Balances, and Compliance](https://techinterview.org/lld-employee-leave-management/)

Related system design: [Low-Level Design: Task Management System — Boards, Workflows, Assignments, Due Dates, and Notifications](https://techinterview.org/lld-task-management-system/)

Related system design: [Advanced Tree Interview Patterns: Segment Trees, Fenwick Trees, Trie Operations, BST Validation (2025)](https://techinterview.org/advanced-tree-interview-patterns/)

Related system design: [System Design: Social Network News Feed — Fan-out on Write vs Read, Ranking, and Feed Generation](https://techinterview.org/system-design-social-network-feed/)

Related system design: [System Design: Typeahead and Search Autocomplete — Trie, Prefix Indexing, and Real-time Suggestions](https://techinterview.org/system-design-typeahead-search-autocomplete/)

Related system design: [Advanced Graph Algorithms Interview Patterns: Bellman-Ford, Floyd-Warshall, Kruskal MST, Tarjan SCC (2025)](https://techinterview.org/advanced-graph-algorithms-interview-patterns/)

Related system design: [Low-Level Design: Document Management System — Versioning, Permissions, Full-text Search, and Collaboration](https://techinterview.org/lld-document-management-system/)

Related system design: [String Matching Algorithm Interview Patterns: KMP, Rabin-Karp, Z-Algorithm, and Boyer-Moore (2025)](https://techinterview.org/string-matching-algorithms-interview-patterns/)

Related system design: [Dynamic Programming on Graphs: Shortest Path DP, DAG DP, and Tree DP (2025)](https://techinterview.org/dynamic-programming-graphs-interview/)

Related system design: [Randomized Algorithms Interview Patterns: Reservoir Sampling, QuickSelect, Skip Lists (2025)](https://techinterview.org/randomized-algorithms-interview/)

Related system design: [Amortized Analysis Interview Patterns: Dynamic Arrays, Stack Operations, and Union-Find (2025)](https://techinterview.org/amortized-analysis-interview/)

Related system design: [System Design: ML Feature Store -- Feature Computation, Storage, Serving, and Point-in-Time Correctness](https://techinterview.org/system-design-ml-feature-store/)

Related system design: [System Design: Distributed Message Queue -- Kafka Architecture, Partitions, Consumer Groups, and Delivery Guarantees](https://techinterview.org/system-design-distributed-message-queue/)

Related system design: [Low-Level Design: Social Media Platform -- Posts, Feeds, Follows, and Notifications](https://techinterview.org/lld-social-media-platform/)

Related system design: [Number Theory Interview Patterns: GCD, Sieve of Eratosthenes, Fast Exponentiation, and Modular Arithmetic (2025)](https://techinterview.org/number-theory-interview-patterns/)

Related system design: [Topological Sort and Strongly Connected Components: Interview Patterns for Directed Graphs (2025)](https://techinterview.org/topological-sort-scc-interview-patterns/)

Related system design: [System Design: Chat Application — Real-Time Messaging, Message Storage, and Presence (WhatsApp/Slack)](https://techinterview.org/system-design-chat-application/)

Related system design: [Palindrome Dynamic Programming Interview Patterns: LPS, Minimum Cuts, and Palindrome Partitioning (2025)](https://techinterview.org/palindrome-dp-interview-patterns/)

Related system design: [Greedy Algorithm Interview Patterns: Activity Selection, Jump Game, and Interval Scheduling (2025)](https://techinterview.org/greedy-interview-patterns/)

Related system design: [System Design: Typeahead and Autocomplete — Trie, Ranking, and Real-Time Suggestion Updates](https://techinterview.org/system-design-typeahead-autocomplete/)

Related system design: [Tree DP and Path Problems: Maximum Path Sum, Diameter, LCA, and Serialization (2025)](https://techinterview.org/tree-dp-path-interview-patterns/)

Related system design: [Divide and Conquer Interview Patterns: Merge Sort Variants, Count Inversions, and Closest Pair (2025)](https://techinterview.org/divide-conquer-interview-patterns/)

Related system design: [Longest Increasing Subsequence (LIS): DP and Binary Search Interview Patterns (2025)](https://techinterview.org/longest-increasing-subsequence-interview-patterns/)

Related system design: [Merge Intervals Interview Patterns: Overlapping Intervals, Meeting Rooms, Calendar Problems (2025)](https://techinterview.org/intervals-merge-interview-patterns/)

Related system design: [System Design: Ad Server — Targeting, Real-Time Bidding, Impression Tracking, and Click Attribution](https://techinterview.org/system-design-ad-server/)

Related system design: [Math Interview Patterns: Prime Sieve, Fast Power, GCD, and Combinatorics (2025)](https://techinterview.org/math-interview-patterns/)

Related system design: [Low-Level Design: Online Learning Platform (Coursera/Udemy) — Courses, Progress, and Certificates](https://techinterview.org/lld-online-learning-platform/)

Related system design: [Graph BFS Interview Patterns: Shortest Path, Islands, Word Ladder, and Multi-Source BFS (2025)](https://techinterview.org/graph-bfs-interview-patterns/)

Related system design: [String Hashing Interview Patterns: Rabin-Karp, Rolling Hash, and Polynomial Hashing (2025)](https://techinterview.org/string-hashing-interview-patterns/)

Related system design: [Low-Level Design: Task Management System (Trello/Jira) — Boards, Workflows, and Notifications](https://techinterview.org/lld-task-management/)

Related system design: [Dynamic Programming Patterns: Recognizing and Solving DP Problems (Complete Guide 2025)](https://techinterview.org/dynamic-programming-patterns/)

Related system design: [Tree Traversal Interview Patterns: Inorder, Level Order, Zigzag, and Serialize/Deserialize (2025)](https://techinterview.org/tree-traversal-patterns/)

Related system design: [DP on Trees Interview Patterns: Subtree DP, Rerooting, and Path Aggregation (2025)](https://techinterview.org/dp-on-trees-interview-patterns/)

Related system design: [Low-Level Design: Collaborative Document Editor — Operational Transform, CRDT, and Conflict Resolution](https://techinterview.org/lld-document-editor/)

Related system design: [System Design: Search Ranking — Query Processing, Inverted Index, and Relevance Scoring](https://techinterview.org/system-design-search-ranking/)

Related system design: [Low-Level Design: Calendar App — Event Scheduling, Recurring Events, and Conflict Detection](https://techinterview.org/lld-calendar-app/)

Related system design: [Union-Find (Disjoint Set Union) Interview Patterns: Path Compression, Connectivity, and Advanced Problems (2025)](https://techinterview.org/graph-union-find-advanced/)

Related system design: [Low-Level Design: CRM System — Contact Management, Pipeline Tracking, and Activity Logging](https://techinterview.org/lld-crm-system/)

Related system design: [Low-Level Design: Job Board Platform — Job Listings, Search, Applications, and Recruiter Workflow](https://techinterview.org/lld-job-board/)

Related system design: [String Algorithm Interview Patterns: KMP, Rabin-Karp, Z-Function, and Trie Applications (2025)](https://techinterview.org/string-algorithms-interview-patterns/)

Related system design: [System Design: Typeahead / Search Autocomplete — Trie Service, Ranking, and Low-Latency Delivery](https://techinterview.org/system-design-typeahead/)

See also: [Low-Level Design: Inventory Management System](https://techinterview.org/lld-inventory-management/)

See also: [Low-Level Design: Warehouse Management System](https://techinterview.org/lld-warehouse-management/)

See also: [Low-Level Design: Online Judge System](https://techinterview.org/lld-online-judge/)

See also: [System Design: Analytics Dashboard](https://techinterview.org/system-design-analytics-dashboard/)

See also: [Low-Level Design: Library Management System](https://techinterview.org/lld-library-system/)

See also: [Advanced Interval Interview Patterns](https://techinterview.org/interval-patterns-advanced/)

See also: [Low-Level Design: Banking System](https://techinterview.org/lld-banking-system/)

See also: [Low-Level Design: Stock Trading Platform](https://techinterview.org/lld-stock-trading/)

See also: [Low-Level Design: Issue Tracker](https://techinterview.org/lld-issue-tracker/)

See also: [Two Pointers Interview Patterns](https://techinterview.org/two-pointers-patterns/)

See also: [System Design: Feed Ranking and Personalization](https://techinterview.org/system-design-feed-ranking/)

See also: [Low-Level Design: Content Management System](https://techinterview.org/lld-cms/)

See also: [String Manipulation Interview Patterns](https://techinterview.org/string-manipulation-patterns/)

See also: [Low-Level Design: Poll and Voting System](https://techinterview.org/lld-poll-voting/)

LinkedIn system design interviews include poll and survey features. Review the full LLD in [Survey Builder Low-Level Design](https://www.techinterview.org/post/3233465257/lld-survey-form-builder/).

LinkedIn interviews test graph algorithms for network analysis. Review advanced patterns in [Advanced Graph Algorithm Interview Patterns](https://www.techinterview.org/post/3233466528/graph-advanced-patterns/).

LinkedIn's Economic Graph uses knowledge graph principles. Review the full system design in [Knowledge Graph System Design](https://www.techinterview.org/post/3233466551/system-design-knowledge-graph/).

LinkedIn interviews include string algorithm problems. Review KMP and rolling hash patterns in [String Search Algorithm Interview Patterns](https://www.techinterview.org/post/3233466576/string-search-patterns/).

LinkedIn interviews test bit manipulation. Review advanced patterns in [Advanced Bit Manipulation Interview Patterns](https://www.techinterview.org/post/3233460816/bit-manipulation-interview-patterns/).

LinkedIn interviews include graph and cycle problems. Review Floyd's and Union-Find patterns in [Graph Cycle Detection Interview Patterns](https://www.techinterview.org/post/3233466623/graph-cycle-detection/).

LinkedIn system design covers real-time collaboration. Review OT and CRDT patterns in [Collaborative Document Editing System Design](https://www.techinterview.org/post/3233466673/system-design-collaborative-doc/).

LinkedIn system design covers professional feed personalization. Review the full LLD in [Social Feed System Low-Level Design](https://www.techinterview.org/post/3233464486/lld-social-media-feed/).

See also: [Low-Level Design: Code Review Tool - Diffs, Comments, Approvals, and CI Integration (2025)](https://www.techinterview.org/post/3233469720/lld-code-review-system/)

LinkedIn system design covers enterprise access control. Review RBAC, ABAC, and ReBAC patterns in [Access Control System Low-Level Design](https://www.techinterview.org/post/3233466780/lld-access-control-system/).

LinkedIn interviews test graph algorithms. Review shortest path patterns for social and routing graphs in [Graph Shortest Path Interview Patterns](https://www.techinterview.org/post/3233463789/shortest-path-algorithm-patterns/).

LinkedIn tests string search patterns. Review trie insert, prefix, and Word Search II in [Trie Interview Patterns](https://www.techinterview.org/post/3233466827/trie-patterns/).

LinkedIn uses typeahead for people search. Review the full autocomplete LLD with ranking and scale in [Search Autocomplete System Low-Level Design](https://www.techinterview.org/post/3233466851/lld-search-autocomplete/).

LinkedIn uses link tracking. Review URL shortener LLD with idempotency and analytics in [URL Shortener System Low-Level Design](https://www.techinterview.org/post/3233466875/lld-url-shortener/).

LinkedIn built Kafka. Review message queue LLD including partitions, consumer groups, and compaction in [Message Queue System Low-Level Design](https://www.techinterview.org/post/3233466901/lld-message-queue/).

LinkedIn tests social graph traversal. Review BFS, connected components, and bipartite check in [Graph Traversal Interview Patterns](https://www.techinterview.org/post/3233466947/graph-traversal-patterns/).

LinkedIn tests priority queue patterns. Review the median finder, top-K, and IPO two-heap in [Advanced Heap Interview Patterns](https://www.techinterview.org/post/3233466971/heap-advanced-patterns/).

LinkedIn search indexes millions of profiles. Review inverted index, BM25 ranking, and sharding in [Search Engine System Low-Level Design](https://www.techinterview.org/post/3233467019/lld-search-engine/).

LinkedIn system design covers people search and autocomplete. Review the typeahead LLD in [Typeahead Search (Autocomplete) System Low-Level Design](https://www.techinterview.org/post/3233472980/lld-search-typeahead/).

LinkedIn system design covers professional social graph. Review the full LLD in [Social Graph System Low-Level Design](https://www.techinterview.org/post/3233467093/lld-social-graph/).

LinkedIn system design covers professional messaging. Review WebSocket routing and read receipts in [Messaging System (Chat) Low-Level Design](https://www.techinterview.org/post/3233467139/lld-messaging-system/).

LinkedIn system design covers ad analytics pipelines. Review the click tracker LLD in [Ad Click Tracker System Low-Level Design](https://www.techinterview.org/post/3233467186/lld-ad-click-tracker/).

LinkedIn system design covers analytics pipelines at scale. Review the full LLD in [Real-Time Analytics Platform Low-Level Design](https://www.techinterview.org/post/3233467211/lld-realtime-analytics/).

LinkedIn system design covers A/B testing infrastructure. Review the full experimentation platform LLD in [A/B Testing Platform Low-Level Design](https://www.techinterview.org/post/3233467235/lld-ab-testing/).

LinkedIn system design covers large-scale analytics pipelines. Review the full LLD in [Data Pipeline System Low-Level Design](https://www.techinterview.org/post/3233473007/lld-data-pipeline-architecture/).

LinkedIn system design covers people search autocomplete. Review the full LLD in [Search Suggestions (Autocomplete) System Low-Level Design](https://www.techinterview.org/post/3233467329/lld-search-suggestions/).

LinkedIn system design covers email notifications. Review the full email delivery LLD in [Email Delivery System Low-Level Design](https://www.techinterview.org/post/3233467425/lld-email-system/).

LinkedIn system design covers ML feature stores for recommendations. Review the full feature store LLD in [Feature Store System Low-Level Design](https://www.techinterview.org/post/3233467472/lld-feature-store/).

LinkedIn system design covers professional messaging. Review the chat system LLD in [Chat System Low-Level Design (WhatsApp / Messenger)](https://www.techinterview.org/post/3233467496/lld-chat-system/).

LinkedIn system design covers full-text search indexing. Review the Elasticsearch design in [Search Indexing System Low-Level Design](https://www.techinterview.org/post/3233467522/lld-search-indexing/).

Notification preference and DND system design is covered in our [Notification Preferences System Low-Level Design](https://www.techinterview.org/post/3233467567/lld-notification-preferences/).

Newsletter and email delivery system design is covered in our [Newsletter System Low-Level Design](https://www.techinterview.org/post/3233467591/lld-newsletter-system/).

Search history and activity tracking design is covered in our [Search History System Low-Level Design](https://www.techinterview.org/post/3233467708/lld-search-history/).

Contact and address book system design is covered in our [Address Book System Low-Level Design](https://www.techinterview.org/post/3233467758/lld-address-book/).

Activity feed system design is covered in our [Activity Feed System Low-Level Design](https://www.techinterview.org/post/3233468622/lld-activity-feed-aggregator/).

Waitlist and invite-based signup design is covered in our [Waitlist System Low-Level Design](https://www.techinterview.org/post/3233467857/lld-waitlist/).

Tagging and skill system design is covered in our [Tagging System Low-Level Design](https://www.techinterview.org/post/3233467861/lld-tagging-system/).

Mentions and professional network notification design is covered in our [Mentions and Notifications System Low-Level Design](https://www.techinterview.org/post/3233467932/lld-mentions-notifications/).

Online presence and status system design is covered in our [Presence System Low-Level Design](https://www.techinterview.org/post/3233467933/lld-presence-system/).

Faceted search and people search design is covered in our [Faceted Search System Low-Level Design](https://www.techinterview.org/post/3233467940/lld-search-filters/).

Feed pagination and cursor-based API design is covered in our [Cursor Pagination Low-Level Design](https://www.techinterview.org/post/3233468056/lld-cursor-pagination/).