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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.
- 9403
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- 11
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Showing 2401–2430 of 9403 results
- CloudflareMediumSoftware EngineerImplement a rule-based rate limiter
Design and implement a multi-rule rate limiter that tracks client request quotas across matching path prefixes using a sliding time window.
Coding & AlgorithmsOnsitesliding-windowdata-structuresdesign - CloudflareEasySoftware EngineerPresent a recent project effectively
This question evaluates communication, leadership, and ownership skills within the Behavioral & Leadership domain by assessing how clearly a software engineer describes a recent project and their individual contributions.
Behavioral & LeadershipHR Screen - Cockroach LabsMediumSoftware EngineerPoint-in-Time Reads from a Timestamped Key-Value Store
Build a versioned key-value store whose reads return the value a key held at a given timestamp: the latest write at or before that time, or an empty string if there is none. Tests choosing a per-key data layout that keeps point-in-time lookups fast across up to 200,000 operations.
Coding & AlgorithmsOnsite - Cockroach LabsMediumSoftware EngineerPresent and Defend an End-to-End Project You Owned: Architecture, Choices, Challenges
A choose-your-own system design round: present a core project you owned end to end at a previous job, then defend its architecture, technology choices and hardest challenges under detailed probing. Tests depth of ownership, trade-off reasoning and the ability to move from a diagram to concrete mechanisms.
System DesignOnsite - CodeiumMediumSoftware EngineerFind the third-largest word by length
This question evaluates proficiency in string and array manipulation, ordering by key metrics (string length), and handling tie-breaking via stable ordering, situated in the Coding & Algorithms domain.
Coding & AlgorithmsOnline Assessment - CognitivMediumMachine Learning EngineerDesign a Real-Time Feature Store
This question evaluates a candidate's ability to design real-time feature store architectures, encompassing competencies in low-latency serving, point-in-time correctness for offline training, streaming ingestion, consistency between online and offline features, handling backfills and late events, and scalable monitoring of data quality and reliability. It is commonly asked to assess systems-design and data-engineering judgment for production-grade ML infrastructure, falls under the ML system design and data engineering domain, and tests both conceptual understanding of trade-offs (consistency, latency) and practical application skills for APIs, storage, and operational design.
ML System DesignTechnical Screen - CognitivMediumMachine Learning EngineerMaintain a Streaming Median
This question evaluates understanding of streaming algorithms and dynamic data structures for maintaining order statistics, along with analysis of time complexity and memory trade-offs.
Coding & AlgorithmsTechnical Screen - CognitivHardSoftware EngineerReason About Duplicate Data and Scaling in Spark
This problem tests the ability to design an idempotent, scalable data deduplication pipeline in Apache Spark while considering distributed systems constraints like data skew and state management.
Software Engineering FundamentalsTechnical ScreenApache SparkDistributed SystemsData Engineering - CohereMediumSoftware EngineerAnswer Enterprise Questions Across Internal and External Sources
Design enterprise AI question answering across internal and external sources with permission-aware retrieval, entity mapping, evidence-grounded synthesis, and freshness controls.
System DesignTechnical Screen - CohereMediumFrontend EngineerBuild a Credit Card Form With Validation and Linked Input Fields
A front-end UI coding question: build a credit card form with card number, name, expiry and security code, where every field is validated and the fields are linked, so the detected card network changes formatting and security-code rules. It tests state design, caret-safe input formatting, error timing, accessibility and safe handling of card data.
Software Engineering FundamentalsOnsite - CohereMediumMachine Learning EngineerBuild an LLM-driven text-game agent
This question tests the ability to design a robust pipeline for an LLM-based agent interacting with a stateful environment, focusing on context management, output validation, and error recovery.
Software Engineering FundamentalsOnsiteLLMPrompt EngineeringSystem Design - CohereMediumMachine Learning EngineerDefend Your Own Research Paper: Experimental Setup, Practicality and Later Work
A research paper round where you present your own published paper to an interviewer who already knows it and questions its weaknesses. Prepare to judge whether the experimental setup was reasonable, whether the results are practical, and what the field has learned since publication, all with specific, honest self-critique.
Machine LearningOnsite - CohereMediumSoftware EngineerDelete One '5' From a Digit String to Get the Largest Number
Given a digit string containing at least one 5, delete exactly one 5 so the remaining string has the largest possible numeric value, keeping any leading zeros. This intern online-assessment problem tests reasoning about how each digit position affects a number and careful handling of repeated digits.
Coding & AlgorithmsOnsite - CohereMediumMachine Learning EngineerDesign How an LLM Detects Questions Beyond Its Training Cutoff and Says So
Design how a large language model recognizes questions that depend on information after its training cutoff and tells the user where its knowledge ends. The question tests data construction for calibrated abstention, prompt versus fine-tuning versus retrieval trade-offs, and evaluating both over-refusal and hallucination.
ML System DesignOnsite - CohereMediumFrontend EngineerDesign Real-Time Comments with Optimistic Updates
Design optimistic real-time comments with temporary identities, idempotent posting, response/event reconciliation, visible failure states, and durable history.
System DesignOther - CohereMediumMachine Learning EngineerDesign a Post-Training Pipeline to Improve a 7B Model's Coding for an Enterprise
Design an end-to-end post-training pipeline that improves a 7B language model's coding ability for an enterprise customer, covering data collection, SFT, RLHF, evaluation, serving and a production feedback loop. The question probes dataset construction, reward model choice and why RLHF is still needed when SFT can learn from preference data.
ML System DesignOnsite - CohereMediumFrontend EngineerDesign a Real-Time Comment System Front End With Optimistic Updates
Front-end system design for a real-time comment feed, centered on optimistic updates: a new comment is appended to the list before the backend confirms it, so the user can keep typing. It tests client state modeling, reconciliation with live echoes, failure and retry handling, ordering, reconnection and rendering performance.
System DesignOnsite - CohereMediumMachine Learning EngineerExplain LLM training, RL, and evaluation
This question tests your conceptual understanding of the end-to-end LLM lifecycle, specifically the transition from raw text pre-training to alignment and evaluation.
Machine LearningOnsiteLLMRLHFPPO - CohereMediumMachine Learning EngineerExplain Top-k and Top-p Decoding
This question tests your conceptual and mathematical understanding of Top-k and Top-p (nucleus) sampling, focusing on how they modify the output probability distribution of autoregressive language models to balance creativity and coherence.
Machine LearningOnsiteNLPGenerative AISampling - CohereMediumMachine Learning EngineerImplement Autoregressive Decoding Strategies
This problem tests your ability to implement common sequence decoding strategies used in large language models by manipulating token probability distributions.
Coding & AlgorithmsOnsiteLLMSamplingSoftmax - CohereMediumMachine Learning EngineerImprove LLM reasoning for a domain task
This problem tests your ability to design a robust pipeline for an LLM-based system that requires multi-step reasoning in a specialized domain (e.g., technical legal analysis or medical diagnosis).
ML System DesignOnsiteLLMReasoningRAG - CohereMediumMachine Learning EngineerReplace a Heuristic Terminal Text Game's Python Logic With LLM Calls
A live coding round: replace the heuristic Python implementation of a terminal text game with one driven by an LLM while keeping the game playable end to end. AI assistants are allowed, but the round judges your own implementation and debugging, including validating model output, fallbacks, and tests with a fake model.
Software Engineering FundamentalsOnsite - CoinbaseMediumSoftware EngineerAnalyze food-delivery data
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Analyze food-delivery data states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsOnsite - CoinbaseMediumSoftware EngineerBuild Task Management Through Records, Search, Assignment, and Completion
Implement an in-memory task management system that tracks task lifecycles, assignments, and deadlines with efficient indexing and querying. Tests data structure design, state management, and multi-field sorting.
Software Engineering FundamentalsOnline Assessmentdata-structureshash-tablesorting - CoinbaseMediumMachine Learning EngineerBuild a baseline classification model from messy data
This question evaluates skills in practical machine learning engineering, including data cleaning, preprocessing, feature selection, handling mixed numeric and categorical features, and baseline model construction for a binary classification task.
Machine LearningOnsite - CoinbaseMediumData ScientistCalculate Conversion Lift CI
This question tests the ability to derive and calculate a confidence interval for the difference in conversion rates between two groups, and to explain how this interval informs a business decision.
Statistics & MathOnsiteStatisticsA/B TestingInference - CoinbaseEasyData ScientistCalculate Expected Users Adopting Wallet Feature
This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Calculate Expected Users Adopting Wallet Feature states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Statistics & MathTechnical Screen - CoinbaseEasyData ScientistCalculate Expected Users Linking Coinbase Wallets
Coinbase probability question covering Bernoulli indicators, expected wallet links, complement rule for at least one success, and conditional probability for two users linking wallets.
Statistics & MathTechnical Screen - CoinbaseMediumData ScientistCalculate a Confidence Interval
This question evaluates a candidate's competency in statistical inference for A/B testing, specifically the construction and interpretation of confidence intervals for differences in proportions, and falls under the Statistics & Math domain relevant to Data Scientist roles; it tests practical application (deriving point estimates and standard errors) alongside conceptual understanding (assumptions behind normal approximation versus exact, score-based, or bootstrap intervals). Interviewers commonly ask this to assess ability to quantify treatment effects, reason about approximation validity and alternative interval methods, and distinguish between absolute and relative lift when reporting experimental results.
Statistics & MathOnsite - CoinbaseEasySoftware EngineerClarify CodeSignal partial credit and score access
This question evaluates understanding of how multi-level coding assessments allocate partial credit for test cases and compute aggregate scores across levels on an online assessment platform, testing competency in assessment logistics and test platform mechanics.
Behavioral & LeadershipOnline Assessment
Cloudflare
Cohere
Coinbase