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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
- Companies
- 11
- Topics
- 8
- Languages
Showing 4471–4500 of 4616 results
- WaymoMediumSoftware EngineerFind Shortest Knight Path
This problem tests the ability to model a constrained movement pattern on a 2D grid as an unweighted graph and efficiently find the shortest path using Breadth-First Search (BFS).
Coding & AlgorithmsTechnical ScreenBFSGraphGrid - WaymoMediumSoftware EngineerFind Shortest Paths to Target Nodes
This question evaluates knowledge of graph algorithms and algorithmic problem-solving, specifically computing shortest paths in weighted directed graphs and handling unreachable targets.
Coding & AlgorithmsTechnical Screen - WaymoMediumSoftware EngineerFind the Best Meeting Point on a Grid
This problem tests your ability to use multi-source Breadth-First Search (BFS) to find a point that minimizes total travel distance across a grid with obstacles.
Coding & AlgorithmsTechnical ScreenBFSGraphGrid - WaymoMediumSoftware EngineerImplement Fibonacci generator, balanced BST, frozenset
This problem tests your understanding of Python generators for sequence generation, the mechanics of tree rotations in self-balancing data structures, and the requirements for implementing immutable, hashable collections.
Coding & AlgorithmsTechnical ScreenPythonGeneratorsBST - WaymoEasyData ScientistImplement K-means and handle train-inference mismatch
This question evaluates understanding and hands-on competency in unsupervised clustering (K-means objective, alternating optimization, initialization strategies, empty-cluster handling, stopping criteria, and computational complexity) and sequence modeling for multi-agent trajectory prediction (input representation, attention/GNN architectures, deterministic vs probabilistic outputs, evaluation metrics, and exposure bias from autoregressive training). It is commonly asked to probe both conceptual understanding and practical implementation skills in the Machine Learning domain, testing optimization and scalability trade-offs as well as model-design and training/inference mismatch considerations at a mix of conceptual and practical application abstraction levels.
Machine LearningTechnical Screen - WaymoMediumData ScientistModel Rare Events with a Log Link and Handle Zero Counts
Explain rare-event log-link models, exposure offsets, zero counts, overdispersion, and the difference between counts and binary outcomes.
Statistics & MathTechnical Screen - WaymoMediumMachine Learning EngineerOptimize Tensor Runtime Kernels
This question evaluates competency in optimizing machine learning framework runtimes for accelerators, covering profiling and performance analysis of tensor kernels, memory layout design, operator scheduling and kernel fusion while weighing trade-offs among throughput, latency, memory usage, numerical correctness, and maintainability.
Software Engineering FundamentalsTechnical Screen - WaymoMediumData ScientistSample Points Uniformly from a Unit Disk
Derive uniform random sampling inside a unit disk, explain the radial distribution, and compare a polar sampler with rejection sampling.
Coding & AlgorithmsTechnical Screen - WaymoMediumData AnalystTop 5 Most Efficient Vehicle Models
This problem tests your ability to aggregate data from multiple tables, calculate performance metrics, and handle common SQL pitfalls like division by zero and NULLs.
Data Manipulation (SQL/Python)Technical ScreenSQLAggregationJoins - WaymoMediumSoftware EngineerValidate a Parent-Child Forest
This problem tests graph theory fundamentals by requiring the validation of a forest structure, specifically checking for cycle-free properties and valid parent-child node connectivity constraints.
Coding & AlgorithmsTechnical ScreenGraph TheoryDFSDSU - WayveEasySoftware EngineerRepair Unsafe C++ Ownership with Smart Pointers
Review a C++ ownership sketch with raw allocations and redesign its interfaces around RAII and appropriately restrictive smart pointers. Discuss factory ownership, copying and moving, exception safety, non-owning access, shared lifetimes, cycles, and polymorphic destruction.
Software Engineering FundamentalsTechnical Screen - WeRideMediumData ScientistCompute window averages and merge intervals
Compute window averages and merge intervals evaluates SQL or pandas logic, joins, grouping, window functions, null handling, edge cases, and validation in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Data Manipulation (SQL/Python)Technical Screen - WeRideMediumSoftware EngineerExpand algebraic expression with distribution
This question evaluates parsing of algebraic expressions, application of the distributive law, string manipulation, and algorithmic reasoning about time and extra-space complexity.
Coding & AlgorithmsTechnical Screen - WeRideMediumSoftware EngineerExplain PhD relevance to software engineering
This question evaluates the candidate's ability to translate PhD research into practical software engineering competencies, including technical skills (programming, algorithms, systems design, data processing), engineering practices (testing, version control, CI/CD), and communication of measurable impact.
Behavioral & LeadershipTechnical Screen - WeRideMediumSoftware EngineerImplement Several Core Algorithmic Components
This problem tests your ability to implement fundamental algorithms, including caching mechanisms, probability transformations, and geometric counting patterns.
Coding & AlgorithmsTechnical ScreenHashMapsLinked-ListsProbability - WeRideMediumSoftware EngineerImplement expression expansion to plus-only form
This question evaluates understanding of expression parsing and algebraic expansion via the distributive property, along with skills in string manipulation, stack-managed state for nested parentheses, and time/space complexity analysis.
Coding & AlgorithmsTechnical Screen - WeRideMediumSoftware EngineerImplement matrix multiplication and fast exponentiation
This question evaluates competency in matrix multiplication, modular arithmetic, and exponentiation algorithms as applied to large-scale numeric computations such as sequence generation.
Coding & AlgorithmsTechnical Screen - WeRideMediumData ScientistTest whether two distributions differ
Test whether two datasets come from the same distribution using univariate and multivariate methods, including KS, categorical tests, classifier two-sample tests, MMD, permutation tests, effect sizes, multiple-testing control, clustering-aware uncertainty, and sampling designs.
Statistics & MathTechnical Screen - Weiss Asset ManagementMediumData ScientistEvaluate and Monitor a Paid Electricity Price Forecast
This problem tests the ability to design an evaluation framework for time-series forecasting models and systematic troubleshooting of performance degradation in an automated trading pipeline.
Analytics & ExperimentationTechnical ScreenTime SeriesBacktestingModel Evaluation - Wells FargoMediumSoftware EngineerBuild Spring Boot POST, PUT, and GET Endpoints
Design and implement RESTful endpoints in Spring Boot for an account resource, covering controller annotations, validation, HTTP status codes, error handling, and MockMvc tests.
Software Engineering FundamentalsTechnical ScreenSpring BootJavaREST API - Wells FargoMediumSoftware EngineerChoose LLMs for Software Engineering Tasks
Design an evaluation, privacy, and integration framework to select and verify Large Language Models for enterprise software engineering tasks.
Software Engineering FundamentalsTechnical ScreenLLM EvaluationSystem DesignSoftware Engineering - Wells FargoHardData ScientistCore Components of an LLM-Based AI Agent and How They Interact
An open question about AI agents asks you to name the components of an agent built around a language model, explain what each one does, and show how they work together to complete a multi-step task. It tests understanding of tools, memory, planning, control loops, guardrails and evaluation.
Machine LearningTechnical Screen - Wells FargoMediumSoftware EngineerDesign Cursor Pagination for a Large Dataset
This problem tests the ability to design a performant, stable pagination system for large datasets using cursor-based navigation instead of offset-based pagination.
System DesignTechnical ScreenPaginationDatabase IndexingAPI Design - Wells FargoMediumData ScientistDesign Excel visuals for risk results
Design Excel visuals for risk results 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 & ExperimentationTechnical Screen - Wells FargoMediumData ScientistEnsure model ethics and governance
Ensure model ethics and governance 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 & LeadershipTechnical Screen - Wells FargoMediumData ScientistExplain PD model validation steps
Explain PD model validation steps 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 LearningTechnical Screen - Wells FargoMediumSoftware EngineerGetting Unblocked When Your Tech Lead Won't Help
This question evaluates your problem-solving maturity, ability to manage dependencies, and communication skills when facing roadblocks caused by unresponsive stakeholders.
Behavioral & LeadershipTechnical ScreenBehavioralConflict ResolutionCommunication - Wells FargoMediumSoftware EngineerJava, Spring & Kafka Fundamentals Deep-Dive
Tests practical knowledge of Java concurrency and memory visibility, Kafka at-least-once delivery and idempotency patterns, and Spring Security context propagation across asynchronous thread boundaries.
Software Engineering FundamentalsTechnical ScreenJavaSpring BootApache Kafka - Wells FargoHardData ScientistOrganizing Code and Repositories: Functions, Classes, Comments, GitHub Files
A software practice question asks how you organize code into functions, classes and files, how and when you write comments, and which files a GitHub repository should and should not contain. It tests modular design judgment, documentation habits, and reproducible, secure project hygiene.
Software Engineering FundamentalsTechnical Screen - Wells FargoMediumSoftware EngineerReason About Kafka Consumers and Partitions
This question tests your understanding of Kafka's consumer group protocol, partition assignment logic, and the mechanics of horizontal scaling in distributed message queues.
Software Engineering FundamentalsTechnical ScreenKafkaDistributed SystemsMessaging
Waymo
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Wells Fargo