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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
- Questions
- 546
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- 11
- Topics
- 8
- Languages
Showing 271–300 of 3640 results
- AmazonMediumApplied ScientistImplement PyTorch training loop
This question evaluates practical implementation skills in PyTorch, focusing on model and device management, batch-wise training mechanics, gradient handling, and optimizer interaction.
Coding & AlgorithmsOnsite - AmazonMediumData ScientistImplement Reservoir Sampling; Analyze Time and Space Complexity
This question evaluates understanding of streaming randomized algorithms and probabilistic reasoning—specifically reservoir sampling—along with analysis of time and space complexity and use of hash-based structures for duplicate detection; it is in the Coding & Algorithms domain and tests both conceptual probability invariants and practical implementation skills. Such problems are commonly asked to gauge a candidate's ability to design one-pass, linear-time solutions for unbounded data streams and to reason about algorithmic correctness and resource bounds in technical interviews.
Coding & AlgorithmsOnsite - AmazonMediumApplied ScientistImplement Top-p (Nucleus) Sampling in NumPy
This problem tests your ability to implement the nucleus sampling algorithm from scratch using NumPy, focusing on probability distribution processing and efficient array masking.
Coding & AlgorithmsOnsiteNumPyNLPProbability - AmazonMediumSoftware EngineerImplement a Min-Priority Queue Without a Library Heap
Tests implementation of a binary min-heap from scratch, including array-based representation, sift-up, and sift-down operations, without relying on built-in priority queue libraries.
Coding & AlgorithmsOnsiteHeapData StructuresDesign - AmazonMediumSoftware EngineerImplement a Single-Node Priority Pub/Sub
This question evaluates understanding of concurrent system design, in-memory publish–subscribe semantics, prioritized delivery ordering, API and data structure selection, and thread-safety within the Software Engineering Fundamentals domain.
Software Engineering FundamentalsOnsite - AmazonMediumData ScientistImplement and Analyze 'Merge k Sorted Lists' Algorithm
This question evaluates algorithm design skills and complexity analysis for merging multiple sorted sequences, measuring proficiency with appropriate data structures, time-space trade-offs, and correctness reasoning.
Coding & AlgorithmsOnsite - AmazonMediumApplied ScientistImplement decoder-only GPT-style transformer
This question evaluates implementation-level mastery of transformer architectures, including multi-head masked self-attention, position-wise feed-forward networks, residual connections, and precise tensor-shape reasoning for a decoder-only language model, within the Coding & Algorithms domain of deep learning and neural network engineering.
Coding & AlgorithmsOnsite - AmazonMediumApplied ScientistImplement integer division without using division
This question evaluates proficiency in implementing low-level integer arithmetic and algorithmic optimization, including correct handling of overflow and edge cases within 32-bit signed integer constraints.
Coding & AlgorithmsOnsite - AmazonMediumApplied ScientistImplement inventory allocation with backorders
Implement inventory allocation with backorders evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsOnsite - AmazonMediumData ScientistImplement list overlap and dense-ranked word frequencies
This question evaluates a data scientist's ability to implement efficient multiset intersection and streaming top-k word-frequency computations, covering duplicate-aware counting, dense-ranking, Unicode handling, and strict time/space constraints.
Coding & AlgorithmsOnsite - AmazonMediumData ScientistImplement streaming k-way merge with constraints
This question evaluates competence in streaming algorithms and resource-constrained algorithm design, specifically implementing a k-way merge over blocking, potentially unbounded integer iterators while preserving stable duplicates and reasoning about time and O(k) space complexity.
Coding & AlgorithmsOnsite - AmazonMediumSoftware EngineerImplement tree left/right views via BFS and DFS
This question evaluates understanding of binary tree traversal techniques and algorithmic reasoning for producing per-depth left and right views, assessing competencies in data structures, traversal ordering, and correctness across edge cases.
Coding & AlgorithmsOnsite - AmazonMediumSoftware EngineerImplement two array-cost minimization algorithms
This question evaluates algorithm design, data structure selection, and complexity analysis by requiring implementations for minimizing total merge cost and for removing a contiguous block to minimize the sum of adjacent absolute differences.
Coding & AlgorithmsOnsite - AmazonMediumSoftware EngineerInfluence a Colleague Who Prefers a Different Approach
Describe influencing a colleague through shared goals, fair comparison, evidence, willingness to revise, and a concrete collaborative decision.
Behavioral & LeadershipOnsite - AmazonMediumProduct ManagerInnovation, Root Cause, and Deadline Management Stories
Practice behavioral PM answers for innovation, root-cause analysis, and urgent deadline management. The guide uses STARL examples with metrics, trade-offs, stakeholder handling, prevention mechanisms, and probe-ready details for interview follow-up questions.
Behavioral & LeadershipOnsite - AmazonMediumFrontend EngineerIntervene When Your Team Is Heading in the Wrong Direction
This question assesses a candidate's ability to identify technical or strategic misalignments within a project and their skill in providing constructive, data-driven feedback while maintaining team cohesion.
Behavioral & LeadershipOnsiteLeadershipCommunicationConflict Resolution - AmazonMediumFrontend EngineerInvestigate a Difficult Problem Until You Found the Root Cause
This question assesses the candidate's ability to systematically troubleshoot complex technical issues, demonstrate technical ownership, and implement long-term solutions rather than quick fixes.
Behavioral & LeadershipOnsiteBehavioralOwnershipDebugging - AmazonMediumSoftware EngineerJukebox That Plays the Most-Requested Song First
Design a request queue where each play takes the song with the most pending requests, with ties going to the most recent request. Tests keeping frequency and recency together so both operations run in O(1).
Coding & AlgorithmsOnsitedesignhash-mapstack - AmazonMediumSoftware EngineerKth Largest Perfect Binary Subtree
This problem tests tree traversal techniques, the ability to validate binary tree properties recursively, and the use of selection algorithms to find order statistics.
Coding & AlgorithmsOnsiteTreesRecursionSorting - AmazonMediumApplied ScientistLLM Fundamentals: Tokenization Design and KL-Regularized SFT
This problem tests your understanding of subword tokenization strategies and the theoretical motivation behind KL-divergence constraints during supervised fine-tuning.
Machine LearningOnsiteLLMTokenizationSFT - AmazonHardProduct ManagerLaunching Alexa in a New-Language Market
Practice launching Alexa in a new language market with product vision, personas, MVP use cases, ASR and NLU quality metrics, data scarcity solutions, localization, privacy regulations, partnerships, GTM, risk mitigation, and launch gates.
Product / Decision MakingOnsite - AmazonMediumSoftware EngineerLeadership Principle Stories: Ownership, Dive Deep, Tight Deadline, Disagree and Commit
Behavioral interview practice built around leadership principles: tell stories about taking ownership beyond your role, diving deep under repeated follow-ups, handling a tight deadline, and disagreeing with a teammate then committing. It tests first-person STAR storytelling, measurable results and mapping each story to the principle asked.
Behavioral & LeadershipOnsite - AmazonMediumSoftware EngineerLeaf Domain Cumulative Scores
This problem tests your ability to model hierarchical data using tree traversal and string manipulation to aggregate cumulative metrics across nested domains.
Coding & AlgorithmsOnsiteHash MapString ManipulationTree Traversal - AmazonMediumSoftware EngineerLearn What You Need to Solve an Unfamiliar Problem
Explain learning through an unfamiliar engineering challenge, with a defined knowledge gap, targeted resources, practical validation, expert feedback, and application.
Behavioral & LeadershipOnsite - AmazonMediumFrontend EngineerLearn and Apply a Front-End Technology Across Devices
This question assesses a candidate's ability to self-teach new technologies and integrate them into a production environment while accounting for cross-platform performance and accessibility constraints.
Behavioral & LeadershipOnsiteBehavioralFrontendSelf-Learning - AmazonMediumSoftware EngineerMake a Difficult Decision Under Competing Constraints
Tests your ability to navigate high-stakes technical or organizational trade-offs where constraints conflict, evaluate options objectively, communicate decisions with transparency, and take ownership of the outcomes.
Behavioral & LeadershipOnsiteBehavioralAmazon Leadership PrinciplesDecision Making - AmazonMediumSoftware EngineerMake an Important Decision Before Every Option Can Be Explored
Explain a time-limited decision by identifying essential evidence, accepted uncertainty, reversible steps, stakeholder communication, and outcome checks.
Behavioral & LeadershipOnsite - AmazonMediumSoftware EngineerMaking a Decision with Missing Data
Tests a candidate's ability to demonstrate Amazon's 'Bias for Action' and 'Are Right, A Lot' leadership principles by executing a calculated, high-impact decision under uncertainty with clear rollback triggers.
Behavioral & LeadershipOnsiteBehavioralBias for ActionDecision Making - AmazonMediumApplied ScientistMean and Variance Through Maximum Likelihood
Derive the maximum likelihood estimators (MLE) for the mean and variance of a univariate Gaussian distribution, and analyze the bias of the resulting variance estimator.
Statistics & MathOnsitemaximum-likelihoodgaussian-distributionbias-variance - AmazonMediumSoftware EngineerMeasure platform success and drive adoption
This question assesses your ability to design a telemetry and feedback system for an internal developer platform to measure adoption, identify friction points, and drive cross-team migration.
System DesignOnsiteTelemetryDeveloper ExperienceMetrics
Amazon