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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
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- 11
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- 8
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Showing 691–720 of 1189 results
- NVIDIAHardSoftware EngineerDesign a URL shortening service
This problem tests your ability to design a high-scale, low-latency URL shortening service that requires distributed ID generation, efficient storage strategies, and high availability.
System DesignOnsiteCachingScalabilityDatabase - NVIDIAMediumSoftware EngineerDesign a Version-Aware Package Download Service That Fetches Missing Dependencies
Design a download service for versioned software packages that, when a user requests a version such as Python 2.7, also fetches every dependency missing from their machine. It tests dependency resolution with version ranges, conflicts with already-installed packages, reliable downloads and installs, and serving large artifacts at scale.
System DesignOnsite - NVIDIAMediumSoftware EngineerDesign a bidirectional data sync dashboard
This question assesses the ability to design a distributed system that synchronizes data between a central dashboard and multiple external third-party services in real-time.
System DesignOnsiteDistributed SystemsAPIsData Consistency - NVIDIAHardSoftware EngineerDesign a distributed multi-user counter
This question evaluates expertise in distributed systems architecture, concurrency control, strong consistency models, idempotency under retries, fault tolerance, leader election, and operational monitoring for high-throughput services.
System DesignTechnical Screen - NVIDIAMediumSoftware EngineerDesign an Autonomous-Vehicle Camera Pipeline and Its Perception System
Design an autonomous-vehicle camera pipeline, from synchronized capture and image signal processing to the perception system that turns multi-camera frames into tracked objects for planning. The question tests time synchronization, zero-copy buffering and back-pressure in real-time C++, latency budgeting, multi-camera fusion and tracking, and fault detection with degraded modes.
System DesignOnsite - NVIDIAMediumSoftware EngineerDesign an Autonomous-Vehicle Perception Pipeline
Tests system design principles for real-time, safety-critical autonomous vehicle perception, focusing on multi-sensor hardware synchronization, zero-copy memory pipelines, bounded-latency neural inference, and fail-operational degradation.
System DesignTechnical ScreenAutonomous VehiclesComputer VisionReal-Time Systems - NVIDIAHardSoftware EngineerDesign an artifact store on K8s and Cassandra
This question evaluates distributed-systems and system-design competencies, including concurrency control for unique-name creation, idempotency and retry semantics, deletion modeling (soft deletes, tombstones, TTL), and read-path consistency, caching and performance when running a Java API on Kubernetes with Cassandra storage.
System DesignTechnical Screen - NVIDIAMediumSoftware EngineerDesign first-time Kubernetes deployment in new cloud
This problem tests your ability to design a foundational Kubernetes infrastructure architecture in a new cloud environment, focusing on secure bootstrapping and operational readiness.
System DesignTechnical ScreenKubernetesCloud ArchitectureInfrastructure as Code - NVIDIAHardSoftware EngineerDesign signals across power and clock domains
An NVIDIA software/hardware engineering onsite system-design question on architecting a control-signal interface that crosses both power and clock domains in a SoC. Covers level shifters and isolation cells with always-on vs. switchable placement, clock-domain-crossing schemes (two-flop synchronizers, pulse-to-toggle, request/ack handshakes, async FIFOs) and their STA/CDC constraints, the same-clock simplification, and the A→B→A feedthrough case with clamp choice, retention, wake-up sequencing, and UPF/CPF low-power signoff.
System DesignOnsite - NVIDIAMediumSoftware EngineerDesign the Control Plane for a Compute Cluster: Host Monitoring + Job Dispatch
Design a distributed control plane for a large compute cluster that ingests high-frequency host health and resource heartbeats while scheduling and dispatching jobs onto healthy hosts. The problem evaluates distributed state management, data modeling under write-heavy loads, failure detection, and high-availability coordinator design.
System DesignTechnical ScreenDistributed SystemsCluster ManagementHigh Throughput - NVIDIAHardSoftware EngineerExplain shader compilers and graphics APIs
This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Explain shader compilers and graphics APIs states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignOnsite - NVIDIAMediumSoftware EngineerMarket a new AI technique
This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Market a new AI technique states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - NVIDIAMediumSoftware EngineerRestaurant Table Reservations: Availability Search and Conflict-Free Booking
System design question asking for a restaurant table reservation service where diners search availability, book, change and cancel, and restaurants manage tables and hours. It tests the data model, preventing double-booking under concurrency, holds and retries, fast availability search and handling booking spikes.
System DesignOther - Nash AIMediumSoftware EngineerDesign OOD for probabilistic Minesweeper
Design OOD for probabilistic Minesweeper 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 - Nash AIMediumSoftware EngineerDesign real-time delivery tracking with async updates
This question tests the ability to design a high-throughput, real-time location tracking system that ensures eventual consistency and correct state representation despite network latency and duplicate events.
System DesignTechnical ScreenScalabilityEvent-DrivenCaching - 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 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 - NetflixMediumSoftware EngineerBuild and optimize a video playlist component
Build and optimize a video playlist component 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 - 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 - NetflixMediumSoftware EngineerDesign Netflix viewport deduplication
This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Design Netflix viewport deduplication states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - 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 - NetflixHardSoftware EngineerDesign a File Backup System
This question evaluates understanding of scalable system design, file synchronization and metadata handling, data consistency, fault tolerance, and performance trade-offs involved in designing a file backup system.
System DesignTechnical Screen - NetflixMediumSoftware EngineerDesign a Job Scheduler for ML Training and Batch Inference on a Shared Cluster
Design a job scheduler for machine learning workloads such as training runs and batch inference on a shared compute cluster with GPUs. It tests requirements gathering, queueing and fairness between teams, gang placement for distributed jobs, preemption and checkpointing, and recovery from node and scheduler failures.
System DesignTechnical Screen - 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 - NetflixMediumSoftware EngineerDesign a Streaming Subscription System: Billing, Plan Changes and Payment Retries
Design the subscription backend of a video streaming service such as Netflix, covering the subscription lifecycle, recurring billing through an external payment provider, mid-cycle upgrades and downgrades, retries of failed charges, and scaling. It tests data modeling, safe payment handling, concurrency between member actions and billing jobs, and keeping entitlement checks fast.
System DesignOther - NetflixEasySoftware EngineerDesign a crash-resilient file system
This question evaluates understanding of durable storage and crash recovery mechanisms in file system design, including metadata consistency, durability guarantees, and operational concerns like performance and space overhead.
System DesignTechnical Screen - 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
NVIDIA
Netflix