practice a little every day, paws crossed ♡
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 1651–1680 of 3640 results
- InstacartMediumSoftware EngineerPivot order-status counts
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Pivot order-status counts states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsOnsite - InstacartMediumSoftware EngineerPivot transactions by date without date libs
This question evaluates proficiency in data manipulation, string-based date handling, aggregation and pivot transformations, along with reasoning about data structures, de-duplication and missing-value filling.
Data Manipulation (SQL/Python)Onsite - InstacartMediumSoftware EngineerReserve Cart Inventory Without Overselling
Design a high-throughput inventory reservation system that locks stock when items are added to a cart, prevents overselling during flash promotions, handles automatic reservation expiration, and scales seamlessly under a 10x traffic spike.
System DesignOnsitesystem-designdistributed-systemsconcurrency - InstacartMediumSoftware EngineerResolve a Variable Through Literal and Reference Assignments
Resolve a target variable through an acyclic chain of named assignments until reaching an integer literal, independent of definition order.
Coding & AlgorithmsOnsite - InstacartMediumSoftware EngineerSenior Behavioral Round: Project Deep Dive, Mentoring, Trade-offs and Disagreement
A senior-level behavioral round covering four themes: a project deep dive, mentoring another engineer, a significant technical trade-off, and a disagreement with a colleague or manager. It tests ownership, depth on decisions, influence without authority and honest reflection on outcomes.
Behavioral & LeadershipOnsite - InstacartMediumSoftware EngineerSolve bank, password, expression algorithm tasks
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Solve bank, password, expression algorithm tasks states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsOnsite - InstacartMediumSoftware EngineerSolve expression evaluator and string decoder
This question evaluates a candidate's ability in parsing, expression evaluation, and nested string decoding, including handling malformed input, character encoding nuances, and large-file streaming considerations.
Coding & AlgorithmsOnsite - InstacartMediumSoftware EngineerSpecify the Lowest Price Across Percentage and Buy-X-Get-Y Discounts
Clarify percentage and buy-x-get-y pricing rules, then reason about the cheapest legal discount combination, quantity thresholds, interactions, and rounding.
Software Engineering FundamentalsOnsite - InstacartHardSoftware EngineerTroubleshoot a production incident end-to-end
Troubleshoot a production incident end-to-end evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignOnsite - IntuitMediumSoftware EngineerAdd an LLM-backed recommendation API to an existing service with RAG and prompting
Add an LLM-powered recommendation endpoint to an existing backend service. Design the request flow, write the actual prompt and its structured output format, and discuss retrieval-augmented generation, hallucination, prompt injection, and how to evaluate and monitor the feature.
ML System DesignOnsite - IntuitEasyData ScientistBuild a predictive model from TurboTax sample data
This problem tests your ability to design an end-to-end predictive modeling pipeline for tax-related data, focusing on feature engineering, handling imbalanced datasets, and selecting appropriate evaluation metrics.
Machine LearningOnsiteClassificationFeature EngineeringImbalanced Data - IntuitEasyProduct AnalystExtract insights from a multi-entry funnel scorecard
This question evaluates a candidate's ability to analyze multistep funnel metrics, handle highly skewed traffic across many access points, and prioritize insights from sparse or long-tail data, testing competencies in product analytics and measurement.
Analytics & ExperimentationOnsite - IntuitEasyProduct AnalystHandle missing and unavailable predictive features
This question evaluates a product analyst's machine learning competencies in diagnosing data quality issues, handling feature availability and training-serving skew, and interpreting counterintuitive correlations, testing both conceptual understanding and practical application for model development and deployment.
Machine LearningOnsite - IntuitMediumSoftware EngineerScale a service you just built: schema trade-offs, new features, indexes, and search
System design deep dive on scaling a service built earlier in the same interview loop. Compare schema options, extend the data model for reviews, ratings, and keyword search, and reason about query performance, indexing, pagination, and when a dedicated search engine is worth adding.
System DesignOnsite - IntuitMediumSoftware EngineerStaff engineer self-presentation, what excites you at work, and your superpowers
Behavioral prompts from a staff software engineer loop: give a short slide presentation on your background, interests, and proudest project, then answer what excites you at work and what your superpowers are. It tests storytelling, ownership, staff-level scope, and self-awareness.
Behavioral & LeadershipOnsite - J.P. MorganMediumSoftware EngineerAnswer common behavioral prompts
Answer common behavioral prompts 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 & LeadershipOnsite - J.P. MorganMediumSoftware EngineerArchitecture and Data-Scaling Trade-offs
This question assesses the ability to articulate trade-offs between architectural styles (monolith vs. microservices) and data storage strategies (sharding vs. replication) in the context of a high-throughput financial system.
Software Engineering FundamentalsOnsiteSystem DesignMicroservicesDatabase - J.P. MorganMediumSoftware EngineerBehavioral: Making Progress When Requirements Are Vague
A behavioral question about how you move forward when requirements are vague or incomplete. It tests how a software engineer clarifies goals with stakeholders, separates assumptions from facts, delivers in small verifiable steps, and handles changes in direction along the way.
Behavioral & LeadershipOnsite - J.P. MorganMediumSoftware EngineerCompute longest palindromic subsequence
This question evaluates understanding of dynamic programming for strings, specifically longest palindromic subsequence concepts such as memoization, bottom-up DP, space optimization and subsequence reconstruction.
Coding & AlgorithmsOnsite - J.P. MorganEasySoftware EngineerDescribe a proud project and conflict
This question evaluates interpersonal and leadership competencies—including communication, teamwork, conflict resolution, accountability, and reflective learning—by probing a candidate's description of a proud project and a conflict with a colleague.
Behavioral & LeadershipOnsite - J.P. MorganMediumSoftware Engineer IIDesign Secure Token Authorization and Large-File Transfer
Design a secure, enterprise-grade file transfer service that supports resumable multi-gigabyte uploads/downloads alongside fine-grained, token-based authorization and key management.
System DesignOnsitesystem-designsecuritydistributed-systems - J.P. MorganMediumSoftware Engineer IIDesign a Multimodal Retrieval-Augmented Generation System
This problem tests the ability to design an end-to-end RAG system capable of processing both text and image inputs while ensuring high retrieval precision, security, and traceability.
ML System DesignOnsiteRAGMultimodalSystem Design - J.P. MorganMediumSoftware EngineerDesign a Rate Limiter: Algorithm Trade-offs, Scalability and Availability
A high-level design question on a rate limiter that compares common limiting algorithms and then scales the chosen one across many servers while staying available. It tests trade-off reasoning about accuracy, memory, burst handling, shared state, and what happens when the limiter's own dependencies fail.
System DesignOnsite - J.P. MorganMediumSoftware EngineerDesign a Reliable Bank Payment System
Design a reliable bank payment system that remains correct across retries, crashes, duplicate requests, and ambiguous external-rail timeouts. Define idempotent APIs, a durable state machine and ledger, transactional handoff, safe reconciliation, invariant monitoring, auditability, and operator remediation.
System DesignOnsite - J.P. MorganMediumSoftware EngineerDesign a Scalable Notification System
This question assesses the ability to design a distributed, asynchronous notification system capable of handling high-throughput multi-channel messaging while maintaining strict delivery guarantees and rate-limiting policies.
System DesignOnsiteScalabilityMessage QueuesDistributed Systems - J.P. MorganMediumSoftware Engineer IIDistinguish AI Skills, Agents, LangChain, and LangGraph
This question tests the architectural understanding of modern LLM-based application frameworks and the distinctions between modular AI components, task-oriented agents, and multi-agent coordination systems.
ML System DesignOnsiteLLMOrchestrationAgentic-Workflows - J.P. MorganMediumSoftware EngineerException Handling in a RESTful Service with @ControllerAdvice
This problem tests your ability to design a centralized exception handling mechanism in a Java Spring environment, ensuring consistent API error responses and proper abstraction of internal implementation details.
Software Engineering FundamentalsOnsiteSpring BootREST APIException Handling - J.P. MorganMediumData ScientistExplain C++ virtual dispatch and object lifetime
This question tests the candidate's understanding of C++ memory management, the mechanics of the virtual method table (vtable), and the importance of virtual destructors in polymorphic inheritance.
Software Engineering FundamentalsOnsiteC++Memory ManagementPolymorphism - J.P. MorganMediumSoftware Engineer IIExplain Python Concurrency, HTTP Update Semantics, Garbage Collection, and Deadlocks
Assess core backend engineering fundamentals including Python concurrency tradeoffs, RESTful update semantics, runtime garbage collection mechanisms, and deadlock prevention strategies.
Software Engineering FundamentalsOnsitepythonconcurrencyrest-api - J.P. MorganMediumSoftware Engineer IIExplain Stack Use Cases and Mutability in Python Containers
This problem tests the understanding of LIFO data structure applications, the implications of object mutability in Python, and the technical constraints imposed by hashability in container types.
Software Engineering FundamentalsOnsitePythonData StructuresMemory Management
Instacart
Intuit
J.P. Morgan