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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 151–180 of 3640 results
- AmazonHardData ScientistDemonstrate leadership in data-driven scenarios
This question evaluates leadership and behavioral competencies alongside core data-science skills such as metric design, statistical validation, experimentation, root-cause analysis, stakeholder management, and cross-functional ownership within a Behavioral & Leadership and Data Science domain.
Behavioral & LeadershipOnsite - AmazonMediumData ScientistDemonstrate leadership under disagreement
This question evaluates leadership competencies in stakeholder management, influence without authority, quantitative risk communication, and decision-making under deadline within a Behavioral & Leadership context for a Data Scientist role.
Behavioral & LeadershipOnsite - AmazonMediumSoftware EngineerDemonstrate leadership with STAR examples
Demonstrate leadership with STAR examples 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 & LeadershipOnsite - AmazonMediumData ScientistDemonstrate problem-solving under resistance
This question evaluates a data scientist's end-to-end problem-solving, cross-functional leadership, stakeholder management, and ability to drive measurable business impact under organizational resistance, covering experimental design, data validation, risk assessment, trade-off decisions, and adoption/verification metrics.
Behavioral & LeadershipOnsite - AmazonMediumSoftware EngineerDescribe Deadline, Mistake, Problem-Solving, and AI Experiences
These prompts evaluate a Software Engineer (Intern)'s time management under tight deadlines, ownership and accountability for mistakes, technical problem-solving depth, and the responsible use of generative AI within the Behavioral & Leadership interview domain.
Behavioral & LeadershipOnsite - AmazonMediumApplied ScientistDescribe a decision with incomplete information
Describe a decision with incomplete information 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 & LeadershipOnsite - AmazonMediumSoftware EngineerDescribe handling deadlines, conflicts, feedback, and ownership
This question evaluates interpersonal and leadership competencies such as prioritization and deadline management, scope negotiation, risk communication, conflict resolution, receptiveness to feedback, ownership, proactive collaboration, and root-cause analysis.
Behavioral & LeadershipOnsite - AmazonMediumSoftware EngineerDescribe projects and handle challenges
This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Describe projects and handle challenges states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipOnsite - AmazonHardData ScientistDesign A/B Test for New Amazon Recommendation Module
Design A/B Test for New Amazon Recommendation Module evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Analytics & ExperimentationOnsite - AmazonMediumSoftware EngineerDesign Faceted Product Search at Large Scale
Design a scalable e-commerce product search engine supporting full-text query matching, multi-attribute filtering, dynamic facet aggregations, and near real-time updates for volatile data like price and inventory.
System DesignOnsiteSearchDistributed SystemsInformation Retrieval - AmazonMediumApplied ScientistDesign LFU cache with distributed extension
This question evaluates understanding of cache design and frequency-based eviction policies, efficient data structures that support O(1) operations, and techniques for approximate frequency estimation and summarization in distributed streaming environments.
Coding & AlgorithmsOnsite - AmazonMediumSoftware EngineerDesign Music Search, Playlists, and Playback Controls
This problem tests the ability to design a scalable music streaming architecture, focusing on data modeling for search indices, conflict resolution in distributed state management, and robust API design for real-time playback control.
System DesignOnsiteDistributed SystemsAPIsConcurrency - AmazonHardSoftware EngineerDesign Thread-Safe Tagging and Bookstore Systems
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 Thread-Safe Tagging and Bookstore Systems states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignOnsite - AmazonHardSoftware EngineerDesign a Core Dump Collection and Analysis System
This problem tests the ability to design a distributed, scalable ingestion and analysis pipeline for massive binary crash files while maintaining system performance and data availability.
System DesignOnsiteDistributed SystemsScalabilityStorage - AmazonMediumFrontend EngineerDesign a Debounced Product Search Box
Design and implement an accessible, resilient product search-as-you-type component featuring debounced requests, race-condition handling via request cancellation, client-side caching, and keyboard navigation.
Software Engineering FundamentalsOnsitefrontendjavascriptreact - AmazonMediumSoftware EngineerDesign a Distributed Cron Job Scheduler
Design a fault-tolerant, horizontally scalable distributed cron scheduler capable of triggering millions of recurring tasks with at-least-once delivery semantics and deterministic run coordination.
System DesignOnsiteDistributed SystemsSchedulingFault Tolerance - AmazonHardSoftware EngineerDesign a Distributed Job Scheduler with Run Logs and Exactly-Once Execution
Design a highly available distributed job scheduler that handles one-time and recurring jobs, collects execution logs, and rigorously addresses the practical boundaries of exactly-once execution.
System DesignOnsitesystem-designdistributed-systemsconcurrency - AmazonHardSoftware EngineerDesign a High-Availability Load Balancer
This problem tests the ability to architect a highly available, scalable Layer 7 load balancer, focusing on fault tolerance, traffic distribution strategies, and system reliability.
System DesignOnsiteDistributed SystemsLoad BalancingHigh Availability - AmazonMediumSoftware EngineerDesign a Linked Queue with Deletion Follow-Ups
Implement a linked-list-based FIFO queue supporting constant-time core operations, extended with value-based deletion methods that correctly maintain queue integrity and pointer boundaries.
Software Engineering FundamentalsOnsitelinked-listqueuedata-structures - AmazonMediumSoftware EngineerDesign a Low-Latency Ad Serving Backend With Targeting, Budgets and Tracking
An Amazon system design question: design an ad server that selects and returns an ad for each page request within a tight latency budget. It covers targeting and candidate retrieval, ranking and auctions, budget enforcement and pacing, impression and click tracking, and failure handling.
System DesignOnsite - AmazonHardData ScientistDesign a Machine Learning Recommendation System Pipeline
Design a Machine Learning Recommendation System Pipeline evaluates core ML concepts, assumptions, math intuition, training/evaluation trade-offs, and practical failure modes in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Machine LearningOnsite - AmazonMediumSoftware EngineerDesign a Multi-Provider Financial Dashboard
Design a financial dashboard that reconciles balances, securities, cryptocurrency, prices, and derived metrics from unreliable external providers. Explain freshness, historical reproducibility, permissions, corrections, outages, and how users can recognize partial or inconsistent data.
System DesignOnsite - AmazonHardApplied ScientistDesign a Multimodal Neural Network
This question evaluates a candidate's competency in designing production-grade multimodal machine learning systems, including architecture choices for text and image encoders, cross-modal fusion strategies, training objectives for joint retrieval and classification, robustness to missing or noisy modalities, and considerations for scalability and low-latency serving. Commonly asked in ML system design interviews to assess both conceptual understanding and practical application of machine learning engineering principles, it falls under the ML System Design domain and probes abilities in model alignment, evaluation metrics, deployment trade-offs, and domain adaptation strategies.
ML System DesignOnsite - AmazonMediumSoftware EngineerDesign a Platform for Training and Serving ML Models
This problem tests the ability to design an end-to-end MLOps platform capable of handling the full lifecycle of machine learning models, from experimentation to production deployment.
ML System DesignOnsiteMLOpsSystem DesignScalability - AmazonMediumSoftware EngineerDesign a Product Image Upload Pipeline for Sellers
Design an asynchronous, distributed image processing and delivery pipeline for an e-commerce seller portal, focusing on direct-to-cloud uploads, state management, moderation workflows, and resilient global caching.
System DesignOnsitesystem-designdistributed-systemsevent-driven - AmazonMediumSoftware EngineerDesign a Ride-Hailing Matching System
This question evaluates competence in large-scale real-time system design, covering high-throughput ingestion and burst absorption, stream deduplication, geospatial indexing, and low-latency matching and caching for ride-hail workflows.
System DesignOnsite - AmazonMediumSoftware EngineerDesign a Scalable Metrics Monitoring System
Design a high-throughput time-series metrics monitoring and alerting platform similar to Amazon CloudWatch, focusing on series identity, cardinality controls, and low-latency aggregations.
System DesignOnsitesystem-designtime-seriesmonitoring - AmazonMediumSoftware EngineerDesign a Scalable and Polite Web Crawler
This question tests the ability to design a distributed, fault-tolerant system that balances high-throughput data collection with ethical crawling constraints and resource efficiency.
System DesignOnsiteDistributed SystemsQueueingData Pipelines - AmazonMediumData ScientistDesign a Scalable, Fault-Tolerant Distributed Order System
This question evaluates system-design and algorithmic competencies, combining distributed-systems concepts — high availability, low-latency architecture, scalability levers, and fault-tolerance mechanisms — with practical binary-tree traversal and time–space complexity analysis.
Coding & AlgorithmsOnsite - AmazonMediumSoftware EngineerDesign a Structure That Returns the Max of the Last k Inserted Numbers
A data structure design question: support inserting numbers into a stream and returning the maximum of the most recent k values. It covers a basic version with complexity analysis, reducing memory to O(k), comparing arrays, hash maps, linked lists and heaps, and building the optimal solution with a monotonic deque.
Software Engineering FundamentalsOnsite
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