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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 2881–2910 of 3640 results
- RampHardSoftware EngineerDesign a Payment-Count Dashboard That Scales with Readers and Updates
Tests candidate's ability to design a real-time, low-latency financial metrics dashboard that evolves from a simple relational database setup to a horizontally scalable, stream-aggregated architecture resilient to duplicate events and counter drift.
System DesignOnsitesystem-designdistributed-systemsstream-processing - RampHardSoftware EngineerDesign a Tunable Recurring-Transaction Detector
Design and implement a configurable, explainable detector that identifies recurring subscription transactions from noisy transaction logs, handling price variations, irregular cadences, and missing cycles.
Software Engineering FundamentalsOnsitealgorithmssystem-designfinancial-data - RampHardSoftware EngineerImplement a Clean In-Memory Transaction Ledger
Design an in-memory double-entry style financial transaction ledger that supports atomic transfers, strict balance invariants, and idempotency key handling.
Software Engineering FundamentalsOnsiteSystem FundamentalsData StructuresIdempotency - RampHardSoftware EngineerImplement and Defend an AI-Assisted Repository Change
Tests your ability to implement a new feature in a simulated unfamiliar codebase using AI tools responsibly, identifying subtle generated bugs, ensuring test coverage, and defending every architectural and implementation decision.
Software Engineering FundamentalsOnsitecode-auditfinancial-ledgerclean-code - RampHardSoftware EngineerPresent a System You Designed
This question tests your ability to articulate a complex technical project, demonstrating architectural decision-making, ownership, and the ability to evaluate trade-offs in a real-world scenario.
Behavioral & LeadershipOnsiteSystem DesignArchitectureLeadership - RampMediumSoftware EngineerSpreadsheet String Concatenation with Dependent Cells
Build a fixed-grid string spreadsheet with concatenation formulas, dependency updates, repeated references, and read-time circular-reference errors.
Coding & AlgorithmsOnsite - RampHardSoftware EngineerTraverse an HTTP Maze with Retry Handling
This problem tests BFS traversal skills combined with state management for handling intermittent network failures and API constraints.
Coding & AlgorithmsOnsiteBFSGraphAPI - RedditMediumMachine Learning EngineerAnalyze CTR Data and Train Model
This problem tests the end-to-end workflow of building a CTR prediction model, focusing on feature engineering for high-cardinality categorical data and handling temporal leakage.
Machine LearningOnsiteFeature EngineeringCTR PredictionData Leakage - RedditEasyData ScientistCollaborate with PM and Eng as DS
This question evaluates a data scientist's cross-functional collaboration, prioritization, ownership, stakeholder management, and influencing skills when engaging with product managers and engineers.
Behavioral & LeadershipOnsite - RedditMediumMachine Learning EngineerDescribe a failure and a success
This question evaluates ownership, communication, accountability, and impact assessment within engineering and machine learning contexts, focusing on incident management, model launches, delivery outcomes, and collaboration.
Behavioral & LeadershipOnsite - RedditEasyData ScientistDesign A/B test for AI chat box
This question tests the ability to define metrics, design an A/B testing framework, and account for potential biases when deploying a new AI-powered chat feature.
Analytics & ExperimentationOnsiteA/B TestingProduct AnalyticsMetrics - RedditMediumMachine Learning EngineerDesign a Comment-Likelihood Prediction System with a Focus on Feature and Model Serving
Design a machine-learning system that predicts how likely a user is to comment on a post, covering label definition, features and model choice, with most of the depth on feature serving and model serving. Tests online and offline feature consistency, feature freshness, latency budgets and safe model deployment.
ML System DesignOnsite - RedditEasySoftware EngineerDesign a game leaderboard service
This question tests the ability to design a high-throughput, low-latency leaderboard service capable of handling frequent rank updates and read requests for millions of active users.
System DesignOnsiteCachingDatabasesScalability - RedditMediumMachine Learning EngineerDesign a video recommendation system
This question evaluates ML system design competencies for a Machine Learning Engineer, covering infrastructure architecture, logging and observability, feature pipelines, model training/evaluation, serving reliability, and privacy-aware data practices within the ML System Design domain.
ML System DesignOnsite - RedditHardMachine Learning EngineerDesign comment ranking
This problem evaluates your ability to design a scalable comment ranking system that balances engagement, relevance, and safety, while addressing the challenges of low-latency inference and data freshness.
ML System DesignOnsiteRankingInformation RetrievalRecommender Systems - RedditMediumSoftware EngineerDesign comment-likelihood prediction platform
This question evaluates a candidate's competency in ML system design and infrastructure, covering feature pipelines, feature store strategy, training/serving consistency, online inference at high QPS, and production monitoring.
ML System DesignOnsite - RedditEasyData ScientistDesign experiment for ads in chat with budgets
This question tests the ability to design an A/B test for a new ad placement in a chat feature while accounting for budget constraints and potential network effects.
Analytics & ExperimentationOnsiteA/B TestingCausal InferenceExperiment Design - RedditHardData ScientistEstimate Incremental Search-Ad Revenue Without an A/B Test
Design an evaluation framework to estimate the incremental search-ad revenue of a small-scale manual pilot, incorporating variance reduction, inference under heavy-tailed revenue, and ecosystem cannibalization.
Analytics & ExperimentationOnsiteexperimentationcausal-inferencead-tech - RedditMediumMachine Learning EngineerExclude Cat- or Dog-Related Comments and All Their Replies by Reader Mode
Given discussion comments that form reply trees, each flagged as being about cats, dogs, both or neither, return every comment a cat person or a dog person should not see, where hiding a comment also hides all of its replies. Tests reasoning over tree structure, edge cases such as missing parents, and complexity analysis.
Coding & AlgorithmsOnsite - RedditMediumSoftware EngineerImplement a sliding-window rate limiter
This problem tests your ability to design a rate-limiting algorithm that calculates traffic volume within a sliding time window to prevent API abuse.
Coding & AlgorithmsOnsiteHash MapSliding WindowRate Limiting - RedditHardMachine Learning EngineerImprove Reddit onboarding
This question evaluates product sense, analytical reasoning, experiment design, and cross-functional leadership in the context of improving first-time user onboarding and activation on a community platform, testing competencies in user research, metric definition, prioritization, and validation.
Behavioral & LeadershipOnsite - RedditEasyData ScientistMeasure impact of ads-manager automation feature
This question tests your ability to design an evaluation framework for a new feature, specifically focusing on causal inference, metric selection, and identifying potential biases in a two-sided marketplace.
Analytics & ExperimentationOnsiteA/B TestingCausal InferenceMetrics - RedditMediumSoftware EngineerMerge Message Context Windows
This problem tests your ability to merge overlapping intervals efficiently using sorting and greedy techniques, a foundational skill for data reconciliation tasks.
Coding & AlgorithmsOnsiteIntervalsSortingGreedy - RedditMediumMachine Learning EngineerModel y from x and interpret distributions
This question evaluates modeling judgment in machine learning, covering problem framing (regression versus classification), baseline model and metric selection, interpretation of feature or class distribution differences, and cold-start strategies for users, items, and regions.
Machine LearningOnsite - RedditEasyData ScientistPrioritize competing engineering requests
This question evaluates a data scientist's prioritization, stakeholder management, trade-off communication, and leadership competencies when balancing competing analytics and experimentation requests.
Behavioral & LeadershipOnsite - RedditHardMachine Learning EngineerSolve palindrome and list tasks
This problem tests your ability to manipulate string prefixes to satisfy palindromic properties and your skill in performing in-place linked list reordering based on node index parity.
Coding & AlgorithmsOnsiteStringLinked ListTwo Pointers - RemitlyHardSoftware EngineerDesign a Production-Ready URL Shortener
This question evaluates competency in designing a scalable, reliable, and secure production URL shortening service, covering API design, link data modeling and analytics, ID/token generation, caching and read/write paths, partitioning/replication/consistency choices, rate limiting and abuse mitigation, TTL handling and cleanup, and HA/DR and monitoring. Commonly asked in system design interviews to probe architectural trade-offs for high-read consumer services, it belongs to the System Design domain and emphasizes practical application of distributed systems and operational concepts rather than only conceptual theory.
System DesignOnsite - RemitlyMediumSoftware EngineerDesign an Elevator System and Scheduler
This question evaluates a candidate's object-oriented design and algorithmic scheduling competencies, focusing on concurrency control, fault tolerance, queue management, tie-breaking rules, and time/space complexity analysis within an elevator control system.
Coding & AlgorithmsOnsite - RemitlyEasySoftware EngineerDesign an IP Address Filtering Service
Design a low-latency service that allows or denies traffic using source or destination IP rules. Candidates must define conflict precedence, address normalization, versioned rollout, stale-state behavior, audit evidence, privacy-conscious logging, and safe rollback.
System DesignOnsite - RemitlyMediumSoftware EngineerSolve k-Nearest Places by Latitude/Longitude
This question evaluates geospatial algorithm and systems-design competencies, focusing on nearest-neighbor search, great-circle distance computation, spatial indexing, and runtime/memory trade-offs for scalable location queries.
Coding & AlgorithmsOnsite
Ramp
Reddit
Remitly