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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 2401–2430 of 3640 results
- NVIDIAMediumSoftware EngineerSolve small string and API tasks
This problem tests your ability to handle nested structural validation using stacks and the design of a robust API integration function that aggregates paginated responses.
Coding & AlgorithmsOnsiteStackStringsAPI - NVIDIAMediumSoftware EngineerStreaming Top-K Frequent Elements with O(1) Updates Instead of a Heap
Design a structure that consumes an unbounded stream and reports the K most frequent elements at any time, first with a heap and then with constant-time updates after the interviewer rejects the heap. It tests per-operation cost analysis, data-structure invariants, deterministic tie handling, and extensions to sliding windows, approximate counting, and sharded streams.
Software Engineering FundamentalsOnsite - NVIDIAHardSoftware EngineerVerification Plan for a FIFO, a Round-Robin Arbiter and a Valid/Ready Handshake
A hardware design-verification interview question: plan how to verify a FIFO, a round-robin arbiter and a valid/ready handshake interface. It tests testbench architecture with scoreboards and reference models, constrained-random stimulus, corner cases, SystemVerilog assertions and functional coverage.
Software Engineering FundamentalsOnsite - NVIDIAEasySoftware EngineerWrite a Tiny Linux Resource Reporter That Flags Usage Spikes
Write a small Linux agent that reads live CPU, memory and disk usage from kernel-exposed files, reports them as JSON to a collector endpoint over HTTP, and adds a rolling-window check that only flags a sustained resource spike rather than a single noisy reading.
Software Engineering FundamentalsOnsitelinuxsystemshttp - NavanMediumSoftware EngineerHow to answer frontend video-screen behavioral prompts
This question evaluates frontend engineering expertise, communication and collaboration skills, and domain-specific competencies such as Angular and scalable SaaS web application experience.
Behavioral & LeadershipOnsite - NavanMediumSoftware EngineerModel booking auxiliary comments with admin updates
This question evaluates object-oriented data modeling, access-control and auditability considerations, and scalable batch-update strategies for reservation-related metadata like auxiliary comments.
System DesignOnsite - NetappMediumSoftware EngineerDesign a Production Retrieval-Augmented Generation Pipeline
This problem tests the ability to design an end-to-end RAG system, focusing on document processing, embedding strategies, retrieval mechanisms, and ensuring accuracy through grounding.
ML System DesignOnsiteRAGLLMVector Database - NetappMediumSoftware EngineerDesign an Ordering Service That Prevents the Last Item from Being Oversold
This question tests the ability to design a high-concurrency reservation system that prevents race conditions and overselling using database transactions and distributed locking strategies.
System DesignOnsiteConcurrencyDistributed SystemsDatabase Transactions - NetappMediumSoftware EngineerIdentify the Orchestrator in a Server Connection Graph
This problem tests graph theory fundamentals by identifying a central hub node in a star-topology network using adjacency properties.
Coding & AlgorithmsOnsiteGraph TheoryData StructuresAlgorithms - NetappMediumSoftware EngineerMerge Two Sorted Singly Linked Lists
This problem tests the ability to manipulate pointers in a singly linked list to perform an in-place merge of two sorted lists.
Coding & AlgorithmsOnsiteLinked ListsPointersRecursion - NetappMediumSoftware EngineerPrioritize Several Simultaneous High-Priority Tasks
This question assesses the candidate's ability to manage competing project demands, utilize objective criteria for prioritization, and communicate effectively with stakeholders under pressure.
Behavioral & LeadershipOnsitePrioritizationCommunicationConflict Resolution - NetappMediumSoftware EngineerRank Teams from Ballot Preferences
This problem tests your ability to manage multi-level sorting criteria by implementing custom comparison logic for an array of preference rankings.
Coding & AlgorithmsOnsiteSortingHash MapGreedy - NetappMediumSoftware EngineerResolve a Conflict Within an Engineering Team
This question assesses the candidate's ability to navigate technical or process-related disagreements within a team, focusing on conflict resolution strategies, interpersonal communication, and long-term project outcomes.
Behavioral & LeadershipOnsiteConflict ResolutionSoft SkillsTeamwork - NetflixMediumData ScientistAddress Fraud Detection with Imbalance and Concept Drift Solutions
Evaluates end-to-end fraud detection ML system design for online payments under drift and imbalance. Strong answers handle delayed labels, class imbalance, feature engineering, cost-sensitive validation, real-time deployment, threshold actions, monitoring, retraining, and concept drift.
Machine LearningOnsite - NetflixMediumData ScientistAggregate D1 retention cohorts in SQL
This question evaluates a candidate's competency in time-series cohort analysis and SQL-based data manipulation, specifically measuring DAU, new-user cohorts, D1 retention and revenue-per-user while handling deduplication and user filtering.
Data Manipulation (SQL/Python)Onsite - NetflixMediumData ScientistAnswer core probability and statistics questions
This question evaluates core probability and statistical inference competencies—covering Bayesian reasoning, regression controls and confounding, the Central Limit Theorem, distribution moments, t-statistics, and effect size/MDE—relevant to quantitative data analysis and hypothesis testing for a Data Scientist role in the Statistics & Math domain.
Statistics & MathOnsite - NetflixHardSoftware EngineerBuild a Recommendation System and Conversational Interface from Scratch
Design an initial recommendation system, then extend it with a chatbot that can retrieve and explain recommendations while respecting the same eligibility and ranking rules. Connect data and model choices to serving architecture, latency and throughput, evaluation, monitoring, failure modes, and iteration.
ML System DesignOnsite - NetflixHardSoftware EngineerCompute Earliest Completion Times
This question evaluates understanding of directed acyclic graphs, dependency resolution, computation of earliest task completion times, and cycle detection within prerequisite relationships.
Coding & AlgorithmsOnsite - NetflixMediumData ScientistCompute ITT, TOT, and LATE with noncompliance
This question evaluates understanding of causal inference and experimental analysis, specifically estimation and interpretation of ITT, TOT, and LATE under noncompliance along with classification of compliance types (compliers, always-takers, never-takers, defiers).
Analytics & ExperimentationOnsite - NetflixHardSoftware EngineerCompute subtree sums with tree DFS
This question evaluates proficiency in tree traversal and aggregation techniques, specifically computing subtree sums using depth-first search while handling traversal state and constraints such as negative values and large n.
Coding & AlgorithmsOnsite - NetflixHardData ScientistDemonstrate handling dismissive stakeholders with candor
This question evaluates a candidate's competency in stakeholder management, candid communication under pressure, conflict de-escalation, requirement elicitation, and outcome-oriented leadership for a Data Scientist role.
Behavioral & LeadershipOnsite - NetflixMediumSoftware EngineerDesign Ad Frequency and Order Tracking
This question tests the ability to design a high-throughput, low-latency distributed counter service for frequency capping and an accurate tracking system for ad order delivery.
System DesignOnsiteScalabilityDistributed SystemsCaching - NetflixHardSoftware EngineerDesign Publisher Configuration Rules
This question evaluates system design skills focused on configuration management and rule-based policy modeling for supply-side advertising platforms, covering inventory modeling, rule inheritance and overrides, conflict resolution, real-time evaluation, and operational controls like validation, versioning, rollout, and auditing.
System DesignOnsite - NetflixMediumSoftware EngineerDesign Rolling-Window Ad Frequency Capping
This question evaluates system-design skills for building scalable, low-latency services that enforce time-based rolling-window state, including data modeling for impression history, read/write paths, concurrency control, and fault tolerance; category: System Design.
System DesignOnsite - NetflixMediumSoftware EngineerDesign a Distributed Frequency-Capping Service
Tests the ability to design an ultra-low latency, highly available counting and rate-limiting system for ad frequency capping across distributed environments, balancing consistency with latency trade-offs.
System DesignOnsiteDistributed SystemsCachingAdTech - NetflixMediumSoftware EngineerDesign a Scheduler for ML Training and Batch Inference Jobs
This question tests the ability to design a distributed job scheduler capable of handling heterogeneous ML workloads with varying priority, resource requirements, and fault-tolerance constraints.
System DesignOnsiteDistributed SystemsSchedulingResource Management - NetflixHardData ScientistDesign a robust conversion propensity model
This question evaluates a candidate's competency in end-to-end propensity modeling, covering correct labeling to avoid post-treatment leakage, time-windowed feature engineering, class-imbalance and calibration strategies, causal uplift estimation, and production concerns such as monitoring, serving consistency, and cold-start scoring.
Machine LearningOnsite - NetflixMediumSoftware EngineerDesign ad frequency capping
This question evaluates a candidate's competence in large-scale system design, including distributed systems, real-time analytics, data modeling, and consistency and scalability trade-offs for ad frequency capping.
System DesignOnsite - NetflixHardSoftware EngineerDesign ads frequency capping service
This question evaluates a candidate's ability to design a low-latency, high-QPS, multi-tenant frequency capping service, testing competencies in identity resolution, hierarchical cap modeling, window semantics, counter and storage architecture, consistency versus latency trade-offs, real-time decisioning APIs, configuration/versioning, backfill, reporting, privacy/compliance, and failure handling. It is commonly asked to assess systems-design proficiency in distributed systems, databases, caching, API design, and operational reliability; it belongs to the System Design domain and emphasizes practical application with system-level conceptual reasoning rather than purely algorithmic detail.
System DesignOnsite - NetflixHardSoftware EngineerDesign an Ad Pacing System
This question evaluates a candidate's skill in designing large-scale, low-latency distributed advertising systems, including pacing algorithms, budgeting and spend tracking, concurrency control, event processing, and observability.
System DesignOnsite
NVIDIA
Netflix