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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.
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Showing 5941–5970 of 9403 results
- NetflixMediumSoftware EngineerFind longest unique show window
This question evaluates concepts in sliding-window algorithms, hash-based duplicate tracking, case-insensitive string handling, and the extension of batch solutions to streaming (online) inputs.
Coding & AlgorithmsTechnical Screen - NetflixMediumSoftware EngineerFind the Longest Run of One Character
Tests linear scan and two-pointer/state-tracking techniques to find the maximum number of consecutive identical characters in an ASCII string using constant auxiliary space.
Coding & AlgorithmsTechnical Screenstringstwo-pointerslinear-scan - NetflixMediumSoftware EngineerFind the Longest Substring Without Repeated Characters
Tests sliding window technique, hash map index tracking, and linear-time constraint optimization on string manipulation.
Coding & AlgorithmsTechnical ScreenSliding WindowTwo PointersHash Table - NetflixMediumSoftware EngineerGroup users by same last K watched movies
This question evaluates competency in set operations, grouping via maps/dictionaries, and algorithmic complexity analysis when comparing suffixes of ordered lists.
Coding & AlgorithmsOnline Assessment - NetflixHardSoftware EngineerHow do you give and receive feedback?
This question evaluates a software engineer's interpersonal competencies, specifically the ability to give and receive constructive feedback, demonstrate emotional intelligence, take ownership, and collaborate across cross-functional teams.
Behavioral & LeadershipOnsite - NetflixMediumData ScientistHow to Design Effective A/B Tests for Onboarding
Evaluates A/B test design for a redesigned onboarding flow in a subscription app. Strong answers define activation, user-level randomization, primary and guardrail metrics, sample size, sequential monitoring, and decisions when activation improves but support burden rises.
Analytics & ExperimentationOnsite - NetflixEasyMachine Learning EngineerHow would you support ML stakeholders?
This question evaluates skills in ML infrastructure, stakeholder management, production monitoring, model iteration optimization, and data governance when collaborating with data science partners.
Behavioral & LeadershipOnsite - NetflixMediumData ScientistIdentify Longest Consecutive Incrementing Watch-Time Sequence
This question evaluates a candidate's ability to design and analyze efficient algorithms for detecting longest consecutive incrementing sequences in unsorted integer arrays, testing understanding of appropriate data structures and time/space complexity trade-offs.
Coding & AlgorithmsOnsite - NetflixMediumSoftware EngineerImplement Cache, Undo, and DFS
This problem tests your ability to combine a Least Recently Used (LRU) cache with a command-based undo system, applied to a hierarchical tree structure traversal.
Coding & AlgorithmsOnsiteLRU CacheDFSUndo Pattern - NetflixMediumSoftware EngineerImplement Caches, Undo, and Traversal
This question evaluates proficiency with data structures, API design, and system-level concerns by combining timed in-memory caching, command undo/redo semantics, and depth-first traversal of a tree; it falls under the Coding & Algorithms domain and is commonly asked to assess practical implementation skills, correctness under edge cases, and the ability to reason about time and space complexity. The level of abstraction spans practical application—designing clean APIs and implementing core logic—while also requiring conceptual understanding of complexity analysis and background cleanup or state-management patterns.
Coding & AlgorithmsOnsite - NetflixMediumMachine Learning EngineerImplement Streaming Word Counter
This question evaluates streaming data processing, string tokenization, and frequency-aggregation competencies, focusing on maintaining accurate counts over incremental text inputs using associative data structures.
Coding & AlgorithmsTechnical Screen - NetflixMediumSoftware EngineerImplement TTL Cache and Tree Balance Reporting
This question evaluates proficiency in designing efficient in-memory data structures and tree algorithms, specifically time-to-live cache behavior (expiration semantics and accurate unexpired counts) and per-node subtree-height computations for balance reporting, and it falls under the Coding & Algorithms domain.
Coding & AlgorithmsOnsite - NetflixEasySoftware EngineerImplement a Key-Value Cache with Per-Entry Expiration
This problem tests the ability to design an in-memory storage system that combines fixed-capacity constraints with time-based invalidation logic.
Software Engineering FundamentalsTechnical ScreenHash MapLinked ListConcurrency - NetflixHardSoftware EngineerImplement a Versioned Key-Value Store
This question evaluates understanding of time-versioned data storage, related data-structure selection, handling of overwrite semantics at equal timestamps, and the ability to reason about correctness and complexity trade-offs.
Coding & AlgorithmsOnsite - NetflixHardData EngineerImplement a Weighted Eviction Cache
This problem tests your ability to design a cache that respects both memory capacity and item weights, requiring an efficient combination of a hash map and a doubly linked list.
Coding & AlgorithmsTechnical ScreenHash MapDoubly Linked ListLRU Cache - NetflixMediumSoftware EngineerImplement an in-memory key-value store with per-key TTL expiration and tests
A coding interview question that asks you to implement an in-memory key-value store whose entries expire after a per-key time-to-live, explain the design as you go, and test it. It tests expiry semantics, overwrite handling, reclaiming memory from keys that are never read again, complexity trade-offs and deterministic tests with a controllable clock.
Software Engineering FundamentalsTechnical Screen - NetflixMediumData ScientistImplement longest increasing subarray with one deletion
This question evaluates proficiency in array algorithms and algorithmic optimization, focusing on handling boundary cases, reconstructing index ranges, and meeting strict O(n) time and O(1) extra-space constraints.
Coding & AlgorithmsOnsite - NetflixMediumSoftware EngineerImplement ordering and undo executor
This question evaluates graph algorithm skills (topological ordering and cycle detection) and software design competencies related to command interfaces, undo semantics, and shared-state management.
Coding & AlgorithmsOnsite - NetflixHardData EngineerImplement phrase search and JSON path
This problem tests your ability to process unstructured text into a searchable index and navigate hierarchical data structures using path patterns.
Coding & AlgorithmsOnsiteInverted IndexString ProcessingRecursion - NetflixMediumSoftware EngineerImplement weighted-eviction cache
This question evaluates understanding and practical implementation of data structures and algorithms for a weighted cache, including weighted eviction policies, use of ordered maps, and time-space complexity analysis.
Coding & AlgorithmsTechnical Screen - NetflixHardMachine Learning EngineerL1 vs L2 Normalization: Definitions, Geometry and When to Use Each
A machine learning fundamentals question asking how L1 normalization differs from L2 normalization of a vector. It tests precise definitions, what each normalized vector represents geometrically, when each is the right choice, and the ability to keep normalization distinct from L1 and L2 regularization.
Machine LearningTechnical Screen - NetflixEasyMachine Learning EngineerML Basics Check: Bayes' Rule, Forward-Pass Arithmetic, KNN and Transformer Concepts
A set of basic machine learning checks: a Bayes' rule posterior with a low base rate, forward-pass and parameter-count arithmetic for small neural networks, and true-or-false concept checks on k-nearest neighbors and Transformer attention. It tests quick, accurate reasoning on core ML fundamentals.
Machine LearningOnline Assessment - NetflixMediumSoftware EngineerModel Direct-Sold DSP Orders
This Software Engineering Fundamentals question evaluates data and domain modeling skills for ad-technology order management, focusing on entities such as advertisers, agencies, orders, line items, targeting, creatives, delivery constraints, tracking events, reporting needs, and configuration versioning.
Software Engineering FundamentalsOnsite - NetflixMediumSoftware EngineerModel ads demand data for reporting
This question tests the ability to design a robust data pipeline and schema for tracking ad performance metrics, focusing on handling event-level data, aggregations, and dimension consistency.
System DesignOnsiteData EngineeringData ModelingETL - NetflixMediumSoftware EngineerModel data for an ads platform
This question evaluates proficiency in data modeling and database schema design for advertising systems, including entity-relationship modeling, privacy-aware user identifier handling, and delivery/tracking log representation.
System DesignOnsite - NetflixMediumSoftware EngineerMovie Playlist With Live Score Updates and No Repeats per Loop, Plus Thread Safety
Implement an in-memory movie playlist in which get returns the highest-scoring movie not yet served in the current loop, starting a new loop once every movie has been served, while scores can change at any time. A follow-up asks where to add locks when many threads call it concurrently.
Software Engineering FundamentalsTechnical Screen - NetflixEasyMachine Learning EngineerMultiply Two Sparse Integer Matrices Given as Dense Grids
Given two integer matrices stored as dense lists of rows in which most entries are zero, return their exact matrix product. It tests handling matrix dimensions correctly and exploiting sparsity to skip work on zero entries while still producing every entry of the result.
Coding & AlgorithmsOnline Assessment - NetflixMediumData ScientistNavigate conflicting signals and ambiguous expectations
This question evaluates a Data Scientist's behavioral and leadership competencies — including adaptability to changing expectations, stakeholder management, prioritization between depth and breadth, decision-making principles, and post-outcome learning — and sits squarely in the Behavioral & Leadership domain.
Behavioral & LeadershipOnsite - NetflixMediumSoftware EngineerPlan Eviction and Cleanup for a Production Cache
This problem tests the design of an in-memory caching system, focusing on memory management, eviction strategies, and concurrency control to ensure high performance and stability.
Software Engineering FundamentalsTechnical ScreenSystem DesignConcurrencyCaching - NetflixMediumSoftware EngineerReason About a Movie Billboard Rotation Component
This problem tests the ability to manage dynamic scheduling and priority updates using balanced binary search trees (ordered maps) while handling concurrency and system scalability.
Software Engineering FundamentalsOnsiteData StructuresConcurrencySystem Design
Netflix