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Software Engineer 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 5311–5340 of 5874 results

  • The Trade DeskMediumSoftware Engineer
    Implement a Cloud Storage Service

    This question evaluates a candidate's ability to implement an in-memory cloud storage system, exercising skills in data structures and stateful API design, string handling and pattern matching, sorting and eviction algorithms, and per-user resource accounting.

    Coding & AlgorithmsOnline Assessment
  • TikTokMediumSoftware Engineer
    Answer common behavioral questions using STAR

    This question assesses the candidate's ability to communicate past professional experiences using the STAR method, focusing on accountability, problem-solving, and collaboration in a high-pressure environment.

    Behavioral & LeadershipTechnical ScreenCommunicationSTAR MethodConflict Resolution
  • TikTokMediumSoftware Engineer
    Answer core Python, CS, DB, and testing questions

    This problem tests foundational software engineering knowledge across Python internals, database indexing, and testing strategy through a multi-part conceptual assessment.

    Software Engineering FundamentalsTechnical ScreenPythonDatabasesSystems Design
  • TikTokMediumSoftware Engineer
    Compute length of longest increasing subsequence

    This question evaluates understanding of subsequences, dynamic programming and algorithmic optimization for array processing, and is categorized under Coding & Algorithms; it emphasizes practical application of algorithm design and complexity analysis rather than purely theoretical knowledge.

    Coding & AlgorithmsTechnical Screen
  • TikTokMediumSoftware Engineer
    Compute pipeline order from dependencies

    This question evaluates understanding of graph algorithms and dependency resolution, specifically topological sorting and cycle detection, along with competence in choosing appropriate data structures and analyzing time/space complexity.

    Coding & AlgorithmsTechnical Screen
  • TikTokMediumSoftware Engineer
    Count deletions making array fair

    This question evaluates proficiency with array manipulation, parity-aware summation, and combinatorial counting when elements are removed, situating it in the Coding & Algorithms domain.

    Coding & AlgorithmsTechnical Screen
  • TikTokMediumSoftware Engineer
    Count distinct island shapes in a grid

    This problem tests grid traversal (DFS/BFS) and the ability to represent spatial structures in a canonical form to identify unique patterns.

    Coding & AlgorithmsTechnical ScreenDFSGraphGrid
  • TikTokMediumSoftware Engineer
    Count islands on a torus grid

    This question evaluates skills in graph and grid algorithms, topology-aware adjacency (torus wrap-around), and maintaining dynamic connectivity under incremental updates.

    Coding & AlgorithmsTechnical Screen
  • TikTokMediumSoftware Engineer
    Delete nodes in linked list and binary tree

    This question evaluates proficiency in mutable data structure operations, specifically linked list node removal and binary tree node replacement/deletion, requiring knowledge of traversal, pointer/reference manipulation, and edge-case handling.

    Coding & AlgorithmsTechnical Screen
  • TikTokMediumSoftware Engineer
    Describe a project you are proud of

    This question evaluates technical leadership, ownership, system design, execution, collaboration, trade-off reasoning, and the ability to demonstrate measurable impact from a software project.

    Behavioral & LeadershipTechnical Screen
  • TikTokMediumSoftware Engineer
    Describe a service performance challenge

    This question evaluates competency in production performance engineering, observability-driven diagnosis, experimentation and impact quantification, as well as leadership in prioritizing trade-offs and risk mitigation.

    Behavioral & LeadershipTechnical Screen
  • TikTokMediumSoftware Engineer
    Describe career plan and teamwork approach

    This question evaluates a candidate's career planning, self-awareness, and teamwork competencies, specifically goal setting, alignment with team priorities, conflict resolution, and collaborative decision-making.

    Behavioral & LeadershipTechnical Screen
  • TikTokMediumSoftware Engineer
    Describe toughest challenge and resolution

    This question evaluates a candidate's problem-solving, leadership, communication, decision-making, and ability to quantify impact when resolving complex technical or organizational challenges.

    Behavioral & LeadershipTechnical Screen
  • TikTokMediumSoftware Engineer
    Design LRU cache with O(1) operations

    This question evaluates a candidate's understanding of data structures and algorithm design, specifically skills in implementing constant-time cache operations, eviction policies, update handling, and concurrency/thread-safety considerations.

    Coding & AlgorithmsTechnical Screen
  • TikTokMediumSoftware Engineer
    Design a distributed key-value store

    This problem tests your ability to design a scalable, fault-tolerant distributed key-value store, focusing on partitioning strategies, replication, and handling node failures.

    System DesignTechnical ScreenDistributed SystemsScalabilityHashing
  • TikTokHardSoftware Engineer
    Design a high-concurrency ticketing system

    TikTok software-engineer system-design interview question: design a high-concurrency ticketing / flash-sale system that survives millions of concurrent purchase attempts with zero oversell. It tests admission control and fairness (virtual waiting room, FIFO vs lottery), atomic inventory allocation with TTL reservations, anti-bot defenses, idempotent order creation, hot-key sharding, the data model and APIs, caching, message queues and delivery semantics, consistency and reconciliation, failure handling, capacity planning, SLOs, load testing, and monitoring.

    System DesignTechnical Screen
  • TikTokHardSoftware Engineer
    Design and explain your project architecture

    A TikTok software-engineer system-design screen that asks you to walk through one of your recent projects end-to-end: architecture diagram, components and data stores, sync vs. async data flows and protocols, scaling and capacity planning, fault tolerance, backpressure, idempotency, observability, and security. It also probes the design trade-offs you made, the real failure modes you hit, the measurable impact, and what you would redesign. Includes a fully worked reference answer plus the scoring rubric.

    System DesignTechnical Screen
  • TikTokEasySoftware Engineer
    Design automated regression tests for an API

    This question assesses the ability to structure a comprehensive automated regression suite for a RESTful API, focusing on test case selection, validation strategies, and maintenance.

    Software Engineering FundamentalsTechnical ScreenAPIQACI/CD
  • TikTokMediumSoftware Engineer
    Design low-latency large-scale hotel booking system

    This question evaluates understanding of large-scale backend and distributed system design, including scalability, high availability, consistency models, concurrency control to prevent double-booking, hotspot mitigation, and protocol trade-offs for low-latency booking and availability flows.

    System DesignTechnical Screen
  • TikTokHardSoftware Engineer
    Design overload protection with load shedding

    Design overload protection with load shedding 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.

    System DesignTechnical Screen
  • TikTokMediumSoftware Engineer
    Design system to detect privacy-leak records

    This question evaluates a candidate's ability to design scalable ML-driven systems for detecting and classifying privacy-sensitive and PII-containing records across structured and unstructured data, testing competencies in data engineering, machine learning (including deep learning and LLM/RAG integrations), system architecture, and privacy/security considerations. It is commonly asked to probe reasoning about functional and non-functional requirements, trade-offs in detection and classification approaches, evaluation metrics like precision and recall, feedback loops and operational scaling, and it falls under ML system design with a practical, application-level focus rather than purely conceptual abstraction.

    ML System DesignTechnical Screen
  • TikTokHardSoftware Engineer
    Design tables from metrics

    This question evaluates analytics data modeling and event-driven warehousing skills, including schema design, metric derivation, partitioning/clustering strategies, and data-quality concerns such as deduplication, late arrivals, and idempotency.

    System DesignTechnical Screen
  • TikTokMediumSoftware Engineer
    Discuss Python mutability, copying, and GIL

    This question evaluates understanding of Python mutability and copying semantics — including how mutable versus immutable objects affect function arguments and container behavior — and knowledge of the Global Interpreter Lock (GIL) and concurrency models.

    Data Manipulation (SQL/Python)Technical Screen
  • TikTokMediumSoftware Engineer
    Explain C++ containers, segfaults, and virtual dispatch

    This question assesses the candidate's deep understanding of C++ memory management, the runtime implementation of polymorphism, and the performance characteristics of standard containers.

    Software Engineering FundamentalsTechnical ScreenC++Memory ManagementPolymorphism
  • TikTokMediumSoftware Engineer
    Explain DPO and construct its training data

    This question evaluates understanding of Direct Preference Optimization (DPO) for fine-tuning large language models, assessing conceptual differences from PPO-based RLHF and the competency to design pairwise preference training datasets.

    Machine LearningTechnical Screen
  • TikTokMediumSoftware Engineer
    Explain Java ConcurrentHashMap and queues

    This question evaluates a candidate's understanding of Java concurrency primitives and concurrent collection implementations, focusing on thread-safety, synchronization mechanisms, lock-free techniques, and blocking versus non-blocking queue behavior.

    Software Engineering FundamentalsTechnical Screen
  • TikTokMediumSoftware Engineer
    Explain Java DI, AOP, and transactions

    This question evaluates understanding of Java framework internals and related competencies including dependency injection, aspect-oriented programming and proxy mechanisms, transaction management, annotation processing, bean lifecycle, classpath scanning, bean scopes, and circular dependency detection or resolution.

    Coding & AlgorithmsTechnical Screen
  • TikTokHardSoftware Engineer
    Explain SRE architecture and troubleshooting scenarios

    This question evaluates a candidate's competency in SRE architecture and reliability engineering, covering Kubernetes fundamentals, pod failure troubleshooting, SLO/SLA/SLI reasoning, multi-layer latency diagnosis, and SQL versus NoSQL trade-offs within the System Design domain.

    System DesignTechnical Screen
  • TikTokEasySoftware Engineer
    Explain TLS Handshakes and HTTPS Traffic Inspection

    Tests understanding of the TLS handshake, asymmetric vs. symmetric cryptography in HTTPS, certificate authority verification, and the mechanics of forward secrecy versus intercepting HTTPS proxies.

    Software Engineering FundamentalsTechnical ScreenNetworkingSecurityTLS/SSL
  • TikTokHardSoftware Engineer
    Explain Your System Architecture

    Explain Your System Architecture 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.

    System DesignOnsite