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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 3811–3840 of 9403 results
- GoogleMediumSoftware EngineerMinimize Direction Violations in a Directed Road Network
Find the minimum number of edge reversals needed to travel from a source node to a target node in a directed graph. Tests graph modeling (0-1 weighted edges), edge cases like parallel edges and disconnected components, and efficient shortest-path traversal.
Coding & AlgorithmsOnsiteGraphBFSShortest Path - GoogleMediumMachine Learning EngineerMinimize Fence Painting Operations
This problem tests your ability to use a greedy approach or dynamic programming to find the minimum number of strokes required to paint a fence of varying heights.
Coding & AlgorithmsTechnical ScreenGreedyStackArrays - GoogleMediumData ScientistMinimize L2, L1, and quantile losses
This question evaluates understanding of statistical estimators and optimization principles for L2, L1, and tilted absolute (quantile) loss functions, including use of derivatives and subgradients, order-statistics, algorithmic complexity, and robustness considerations.
Coding & AlgorithmsTechnical Screen - GoogleHardSoftware EngineerMinimize maximum height along a grid path
This problem tests your ability to adapt shortest-path algorithms, such as Dijkstra's or Binary Search on the answer, to minimize the maximum edge/node weight along a path.
Coding & AlgorithmsTechnical ScreenGraphDijkstraBinary Search - GoogleMediumSoftware EngineerMinimum Cars for Rental Requests
Determine the minimum number of rental cars required to service a given list of booking requests with half-open time intervals.
Coding & AlgorithmsOnsiteintervalsheapgreedy - GoogleMediumSoftware EngineerMinimum Path Node Count with an Optional Broken Vertex
Find the minimum number of vertices on a path between two nodes in an unweighted graph while avoiding a designated broken vertex.
Coding & AlgorithmsOnsitegraphbfsshortest-path - GoogleHardData ScientistModel Soccer Shot Conversion
This problem tests the ability to design an end-to-end predictive model for sports events, focusing on feature engineering, handling spatial data sparsity, and evaluating probabilistic outputs.
Machine LearningTechnical ScreenLogistic RegressionModel CalibrationFeature Engineering - GoogleMediumSoftware EngineerMost Active Users in a Live Communication Stream
This problem tests your ability to efficiently manage and rank real-time event counts using hash maps and balanced data structures or heaps, focusing on deduplication and stream processing.
Coding & AlgorithmsOnsiteHash MapsStream ProcessingData Structures - GoogleMediumData ScientistNarrow a confidence interval for a mean
This question evaluates understanding of confidence intervals, the relationship between sample size and interval width, variance-reduction techniques, the impact of changing confidence levels, and the ability to communicate statistical risk and design-based trade-offs.
Statistics & MathTechnical Screen - GoogleMediumSoftware EngineerNavigate Disagreement, Mistakes, and Difficult Stakeholders
This question tests your ability to navigate professional interpersonal challenges by focusing on conflict resolution, accountability, and the synthesis of technical and human-centric problem-solving.
Behavioral & LeadershipTechnical ScreenCommunicationConflict ResolutionLeadership - GoogleMediumData ScientistNormalize Columns in Binomial Matrix Efficiently
This question evaluates proficiency in matrix manipulation, handling of binomial random samples, column normalization, and algorithmic efficiency for processing large numerical arrays.
Coding & AlgorithmsTechnical Screen - GoogleMediumSoftware EngineerOptimize 0/1 to bounded knapsack DP
This question evaluates mastery of dynamic programming for knapsack problems, focusing on state formulation, space-time optimization, and reconstructing optimal item sets.
Coding & AlgorithmsOnsite - GoogleMediumSoftware EngineerParse a Nested-List String and Compute Its Weighted Sum
Implement a parser that processes a string representation of a nested list and computes the depth-weighted sum of all non-negative integers contained within it.
Coding & AlgorithmsOnsiteString ParsingStackSimulation - GoogleMediumSoftware EngineerParse strings and find meeting slots
This question evaluates string parsing and data-extraction skills alongside set/array-based aggregation and algorithmic reasoning for calendar availability and time-window constraints.
Coding & AlgorithmsOnsite - GoogleHardData ScientistPredict and act on contract renewal risk
This question evaluates competency in applied machine learning for enterprise churn prediction, testing skills in problem framing, feature engineering, model selection, data hygiene, evaluation metrics, and decisioning within the Machine Learning domain.
Machine LearningTechnical Screen - GoogleMediumSoftware EngineerPredict the Most Frequent Next Word in Constant Time
Design and implement a next-word prediction class that builds transition frequencies from adjacent words in sequences and returns the most likely successor for a given word in average constant time.
Coding & AlgorithmsOnsiteHash TableDesignString - GoogleEasyMachine Learning EngineerPresent and Defend Your Research, Then Explain Your Research Interests
A research-focused interview question with no coding: introduce your own research, defend the details of a project under the interviewer's follow-up questions, and explain which research directions interest you. It tests problem framing, ownership of contributions, rigor in evaluation and fit with the team's work.
Behavioral & LeadershipTechnical Screen - GoogleMediumSoftware EngineerProcess Sharded Login Logs
This problem tests your ability to design a robust data pipeline for processing sharded, potentially out-of-order login logs from a distributed system.
Software Engineering FundamentalsOnsiteDistributed SystemsStream ProcessingData Structures - GoogleMediumProduct ManagerProduct Critique & Improvement
Practice a product critique and improvement interview case with a Spotify-style example covering product strengths, pain points, concrete UX changes, metrics, hypotheses, experiments, guardrails, prioritization, and business impact.
Product / Decision MakingTechnical Screen - GoogleMediumSoftware EngineerProject Deep Dive, Collaboration and Project Management, and Conflict Trade-offs
A behavioral interview covering three areas: a deep dive into a project the candidate worked on, collaboration and project management with other contributors, and a conflict that involved a technical or project trade-off. It tests ownership, technical depth under follow-up questions, coordination habits, and how disagreements get resolved.
Behavioral & LeadershipTechnical Screen - GoogleHardSoftware EngineerProject Deep Dive: Kafka Streaming, Redis Caching, and a Go Edge API Gateway
A resume deep dive from a software engineering intern screen: explain a Kafka streaming architecture and Redis caching from past backend work, then defend choosing Go for a distributed edge API gateway and explain how its latency was managed. Tests ownership, trade-off reasoning and failure handling.
Software Engineering FundamentalsTechnical Screen - GoogleHardProduct ManagerProject Leadership Deep Dive
Practice a PM project leadership deep dive covering end-to-end walkthrough, metrics, technical conflict, customer expectation management, cost trade-offs, influence without authority, self-reflection, and executive storytelling. The guide shows how to make one project credible at both VP-summary and detailed-probe levels.
Behavioral & LeadershipOnsite - GoogleMediumData ScientistProve OLS invariance to linear transforms
This question evaluates understanding of linear regression invariance under invertible linear transformations, multivariate linear algebra, and the impact of regularization (ridge and lasso) on coefficient and prediction stability in the Statistics & Math domain.
Statistics & MathTechnical Screen - GoogleMediumData ScientistReading a Regression Slope: P-values, Intervals, and Causality
Use a fitted slope from a one-predictor regression to explain precisely what a p-value and a confidence interval mean, what assumptions they rest on, how confidence and prediction intervals differ, and why significance is not causation. Tests statistical precision under interview pressure.
Statistics & MathOnsitestatisticslinear-regressionhypothesis-testing - GoogleHardProduct ManagerReading-Time Estimation for Google Docs
Practice designing a Google Docs reading-time estimate feature. The solution covers baseline word-per-minute modeling, adjustments for tables, images, comments, language, readability, personalization, privacy-preserving validation, client/backend/data architecture, product surfaces, success metrics, and latency guardrails.
Product / Decision MakingOnsite - GoogleMediumProduct ManagerReal-Time Google Maps Photos — New Product Ideation
Practice a Google Maps real-time street imagery product design case covering target users, jobs to be done, live curb and hazard use cases, MVP scope, metrics, privacy safeguards, safety guardrails, and phased rollout.
Product / Decision MakingTechnical Screen - GoogleMediumSoftware EngineerRearrange Tasks With Cooldown
This problem tests your ability to manage dependencies and scheduling constraints using a greedy strategy with a priority queue.
Coding & AlgorithmsTechnical ScreenGreedyPriority QueueHash Map - GoogleMediumSoftware EngineerReason About an Endpoint-Only Interval Score
This problem tests the understanding of interval arithmetic properties and algorithmic implementation of selection logic in the presence of tied boundary indices.
Software Engineering FundamentalsOnsiteArraysMathOptimization - GoogleMediumData ScientistReflect on a failed decision and redo it
This question evaluates decision-making, ownership, risk assessment, stakeholder management, product impact analysis, and post‑mortem reflection competencies relevant to data scientists.
Behavioral & LeadershipOnsite - GoogleHardSoftware EngineerRepeatedly Delete Leaves Matching a Target Value From a Binary Tree
Remove every binary-tree leaf whose value equals a target, repeating as parents turn into matching leaves, and return the possibly empty result in level-order form. It tests reasoning about cascading deletions, correct handling of the root, and edge cases such as matching internal nodes that keep a child.
Coding & AlgorithmsTechnical Screen
Google