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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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- 11
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Showing 5971–6000 of 9403 results
- NetflixMediumSoftware EngineerRecommend New Friends from a Mutual-Friendship Graph and Scale the Approach
A problem-solving question about recommending new friends from a mutual friendship graph, worked mostly through discussion with a little code and pseudocode. It tests candidate generation and scoring with deterministic tie-breaks, cost in terms of node degree, handling highly connected users, and precomputing and refreshing suggestions at scale.
Software Engineering FundamentalsOther - NetflixMediumSoftware EngineerReport Tree Levels and Balanced Subtrees
Tests traversing a binary tree stored in array (heap) layout to compute subtree heights and identify nodes rooted at height-balanced subtrees along with their tree levels.
Coding & AlgorithmsOnsitebinary-treeheapdepth-first-search - NetflixMediumSoftware EngineerReturn the longest contiguous subarray with all distinct values
This problem tests your ability to use the sliding window pattern and a hash map to maintain a range of unique elements efficiently in O(n) time.
Coding & AlgorithmsTechnical ScreenSliding WindowHash MapArrays - NetflixMediumSoftware EngineerReturn valid task order from prerequisites
This question evaluates proficiency in graph algorithms, notably topological sorting and cycle detection, as well as algorithmic complexity analysis and handling of dependency constraints.
Coding & AlgorithmsOnsite - NetflixHardMachine Learning EngineerReview a Feature Pipeline PR for Production Risks, Then Serve Features by Freshness
Review a feature pipeline pull request whose tests all pass and explain what could break once it runs in production, from time leakage and training-serving skew to data quality and scale. Then decide how the same features should be served when the model needs day-old, minute-fresh or request-time values.
ML System DesignTechnical Screen - NetflixMediumSoftware EngineerSession Token Cache With Per-Entry Expiry and a Test Suite
Implement an in-memory cache whose entries expire individually, reclaim memory for keys that are never read again, and prove it with deterministic tests using an injected clock. Tests expiry semantics, stale-entry handling and test design.
Software Engineering FundamentalsTechnical Screendata-structuresheapcaching - NetflixMediumSoftware EngineerShow Behavioral Fit and Experience
Show Behavioral Fit and Experience evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipHR Screen - NetflixMediumSoftware EngineerShow role fit using past ad experience
This question evaluates a candidate's ability to demonstrate role fit by mapping past ads engineering projects to job requirements and communicating measurable impact, assessing competencies such as ownership, cross-functional collaboration, incident debugging, and prioritization.
Behavioral & LeadershipOnsite - NetflixMediumSoftware EngineerSimulate a TTL Cache with LRU Eviction
Implement a fixed-capacity key-value cache combining per-key TTL expiration with LRU eviction and O(1) average time per operation.
Coding & AlgorithmsTechnical ScreenCacheLRUHash Table - NetflixEasyData ScientistSolve core probability and statistics questions
This problem tests your understanding of the Central Limit Theorem and its application in power analysis for A/B testing and confidence interval estimation.
Statistics & MathOnsiteProbabilityA/B TestingCentral Limit Theorem - NetflixMediumSoftware EngineerSolve non-repeating show substring
This question evaluates understanding of sequence processing, uniqueness detection, and the use of auxiliary data structures to track previously seen elements when finding non-repeating contiguous subsequences, applied to show names instead of characters.
Coding & AlgorithmsTechnical Screen - NetflixMediumSoftware EngineerSolve sliding-window and disjoint-string-pairs tasks
This question tests the ability to combine sliding window techniques with bit manipulation or frequency counting to identify pairs of substrings that share no common characters.
Coding & AlgorithmsTechnical ScreenStringsBit ManipulationSliding Window - NetflixMediumMachine Learning EngineerTransform flat keys into nested dictionary
This question evaluates proficiency in parsing and restructuring hierarchical parameter keys into nested dictionary structures, string manipulation for grouping, handling nonconforming keys and duplicates, and reasoning about time and space complexity.
Data Manipulation (SQL/Python)Technical Screen - NetflixMediumData ScientistWrite SQL for rolling frequency caps
This question evaluates proficiency with rolling-window analytics, frequency cap logic, time-based attribution, and per-user/per-campaign aggregation for advertising data.
Data Manipulation (SQL/Python)Onsite - New RelicMediumBackend EngineerCompress a String by Run-Length Counts, Keeping the Original When Not Shorter
Implement run-length string compression that replaces each run of repeated characters with the character and its count, returning the original string when the compressed form is not strictly shorter. Tests careful run handling, multi-digit counts, the tie rule, and complexity and edge-case discussion.
Coding & AlgorithmsOnsite - New RelicMediumBackend EngineerDesign a Kafka Consumer Service That Groups Trace Events by Trace ID
Design a distributed service that consumes trace events from Kafka, groups every event sharing a trace ID, and hands each complete trace to an existing processing function. Covers partitioning, in-memory versus external state, deciding when a trace is complete, and traces that stay open for hours.
System DesignOnsite - New RelicMediumBackend EngineerLongest Strictly Increasing Path in a Grid with Four-Directional Moves
Given an integer matrix, find the number of cells on the longest path whose values strictly increase, moving only up, down, left, or right with no diagonal steps and no wrap-around at the edges. Tests grid search and the ability to turn a working first solution into an efficient one.
Coding & AlgorithmsOnsite - NewrelicHardSoftware EngineerMaximum Path Sum in an Indexed Binary Tree
This problem tests tree traversal techniques on an index-based representation, focusing on handling negative weights and memory efficiency via an iterative post-order approach.
Coding & AlgorithmsTechnical ScreenBinary TreeDynamic ProgrammingIterative Traversal - NewrelicHardSoftware EngineerProduct of Array Except Self Without Division
This problem tests array manipulation skills and the ability to optimize space complexity by using prefix and suffix product passes instead of division.
Coding & AlgorithmsTechnical ScreenArraysPrefix-SumOptimization - NewsBreakMediumMachine Learning EngineerDerive and implement calibration via temperature scaling
This interview question evaluates core ML concepts, assumptions, math intuition, training/evaluation trade-offs, and practical failure modes in a realistic interview setting. A strong answer for Derive and implement calibration via temperature scaling states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Machine LearningTechnical Screen - NewsBreakHardMachine Learning EngineerDesign approach for class imbalance
This interview question evaluates core ML concepts, assumptions, math intuition, training/evaluation trade-offs, and practical failure modes in a realistic interview setting. A strong answer for Design approach for class imbalance states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Machine LearningTechnical Screen - NewsBreakMediumSoftware EngineerFind Optimal Piecewise Constant Regression Parameters
This problem tests the ability to derive optimal constants for a piecewise regression model with a single split point and to implement an efficient search algorithm to minimize the sum of squared errors.
Machine LearningTechnical ScreenRegressionOptimizationPrefix Sums - NewsBreakMediumMachine Learning EngineerWalk through a key project
This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Walk through a key project states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipTechnical Screen - NexonMediumProduct ManagerHandle Partner Pushback
Answer a game PM behavioral question about handling cross-functional pushback from design, engineering, analytics, publishing, and monetization partners. The solution uses STAR structure, active listening, shared goals, player data, MVP options, guardrails, and decision clarity.
Behavioral & LeadershipTechnical Screen - NexonMediumProduct ManagerInvestigate Item Usage Spike
Investigate an in-game item usage spike by verifying instrumentation, segmenting players and item sources, building hypotheses across patches, economy shifts, promotions, exploits, and bots, then choosing actions with retention, economy, monetization, and trust guardrails.
Product / Decision MakingTechnical Screen - NexonEasyProduct ManagerWalk Through Your Background and Motivation
Prepare Nexon PM background and motivation answers with a coherent career story, game-product relevance, STAR project examples, strengths, weaknesses, player outcomes, live-service thinking, and cross-functional product judgment.
Behavioral & LeadershipHR Screen - NextdoorMediumMachine Learning EngineerAnswer HR motivation and project experience questions
This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Answer HR motivation and project experience questions states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipTechnical Screen - NextdoorMediumMachine Learning EngineerBuild Ranked Feed With Photo Batching
This question evaluates algorithmic reasoning and data manipulation skills, including stable sorting, grouping/batching, and merging of ranked items while preserving ordering invariants.
Coding & AlgorithmsTechnical Screen - NextdoorMediumMachine Learning EngineerBuild a model using only pandas/numpy
This question evaluates proficiency in applied machine learning competencies including data preprocessing, categorical encoding, feature scaling, implementing baseline models and optimization using numpy/pandas, and selecting appropriate evaluation metrics.
Machine LearningTechnical Screen - NextdoorMediumMachine Learning EngineerBuild an end-to-end ML classification pipeline
This question evaluates a candidate's competency in building end-to-end tabular classification pipelines, including data loading and splitting, missing-value handling, categorical encoding, feature scaling, model training and comparison, hyperparameter tuning, metric-based evaluation, model persistence, and batch inference.
ML System DesignTechnical Screen
Netflix
Nextdoor