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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 6991–7020 of 9403 results
- PinterestMediumMachine Learning EngineerSolve prefix, array, and string problems
This problem tests your ability to efficiently manage prefix-based string searching using a Trie data structure, specifically focusing on handling wildcard character matching.
Coding & AlgorithmsOnsiteTrieStringRecursion - PinterestMediumSoftware EngineerSolve set equality and ad log top‑K
This multi-part question evaluates set and multiset operations, frequency counting, top-K computation over time windows, sliding-window and streaming data structures, and character-multiset matching for string construction within the coding & algorithms domain.
Coding & AlgorithmsOnsite - PinterestHardMachine Learning EngineerSupport room moves and query top-k fastest
This problem tests your ability to design a data structure that efficiently manages room assignments and retrieves the top-k rooms based on a primary priority (number of people) and a secondary priority (earliest arrival time).
Coding & AlgorithmsOnsiteData StructuresHeapHash Map - PinterestMediumSoftware EngineerTrack a User's Top Trending Viewed Pin Within a Sliding Time Window
A data structure design exercise: track the Pins a user has viewed within a sliding time window and, at any moment, return the one with the highest trending score. It asks for methods to add a viewed Pin, remove expired Pins and query the top Pin, plus the runtime complexity of each operation.
Software Engineering FundamentalsOnsite - PinterestMediumData ScientistTransform nested dicts with pandas apply/lambda
This question evaluates proficiency in pandas-based data manipulation, including flattening nested list and dict structures, parsing nested attributes, computing per-user aggregates and segment metrics, and implementing robust, vectorized extraction logic that handles missing keys and avoids SettingWithCopy pitfalls.
Data Manipulation (SQL/Python)Onsite - PinterestHardData ScientistVerify Machine-Learning Fundamentals for E-commerce Recommendation Platform
This interview question evaluates core ML concepts, assumptions, math intuition, training/evaluation trade-offs, and practical failure modes in a realistic interview setting. A strong answer for Verify Machine-Learning Fundamentals for E-commerce Recommendation Platform states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Machine LearningOnsite - PinterestMediumData ScientistWrite Queries for Pinterest Engagement Tasks
This question evaluates SQL-based data manipulation and Python set/co-occurrence computation skills, covering aggregation, joins, timestamp-based cohorting and windowing, freshness detection, CTR calculation, and similarity scoring within a data scientist context.
Data Manipulation (SQL/Python)Technical Screen - PinterestMediumData ScientistWrite SQL to compute max-overlap lists
This question evaluates proficiency in SQL data manipulation and set-based operations, focusing on deduplication, pairwise aggregation, and similarity metric computation (Jaccard) over relational tables.
Data Manipulation (SQL/Python)Onsite - PinterestMediumData ScientistWrite SQL to rank categories by impressions
This question evaluates proficiency in SQL data manipulation—covering joins, aggregations, grouping, tie-breaking, date-window logic, and scalability considerations such as indexing and query performance—in the Data Manipulation (SQL/Python) domain.
Data Manipulation (SQL/Python)Onsite - PinterestMediumData ScientistWrite windowed retention and ARPU SQL
This question evaluates proficiency with SQL window functions, joins, aggregations and time-windowed analytics for computing retention and ARPU, as well as handling date truncation, UTC day boundaries and common data edge cases across user, session, and order tables.
Data Manipulation (SQL/Python)Onsite - PitchbookEasySoftware EngineerImplement Euclidean distance and k-nearest neighbors
This question evaluates understanding of Euclidean distance metrics, vector arithmetic, and nearest-neighbor retrieval, testing implementation skills for computing distances and selecting the k closest points.
Coding & AlgorithmsOnsite - PlaidMediumSoftware EngineerCalculate Ordered Job Makespan Across Parallel Workers
Calculate the total makespan required to process a queue of ordered jobs across a fixed pool of identical parallel workers.
Coding & AlgorithmsTechnical ScreenHeapGreedySimulation - PlaidMediumSoftware EngineerCompute discounted prices in a queue
This question evaluates proficiency in array processing, algorithm design, use of auxiliary data structures such as monotonic stacks, and formal complexity and correctness reasoning.
Coding & AlgorithmsTechnical Screen - PlaidMediumSoftware EngineerCount Completed Jobs in a Serial Multi-Worker Pipeline
Calculate the total number of jobs completed by a given deadline across a multi-stage pipelined system with worker pools. The solution requires simulating stage-by-stage batch execution, tracking wave durations, and enforcing barrier synchronization between stages.
Coding & AlgorithmsTechnical ScreenSimulationDynamic ProgrammingQueue - PlaidMediumSoftware EngineerCount Completed Jobs in a Serial Single-Worker Pipeline
Determine the total number of jobs completed by a single worker executing a sequence of stage-gated tasks before a time limit expires. Tests linear simulation, division/modulo arithmetic, handling of zero-duration and zero-count edge cases, and 64-bit integer safety.
Coding & AlgorithmsTechnical ScreenSimulationMathGreedy - PlaidMediumMachine Learning EngineerDesign RAG Evaluation and Debugging
Design a comprehensive evaluation, monitoring, and debugging framework for a production Retrieval-Augmented Generation (RAG) system operating in a high-stakes financial data domain. The candidate must address multi-stage metrics, CI/CD regression testing, and root-cause localization for retrieval vs. generation failures.
ML System DesignOnsiteRAGLLM EvaluationModel Monitoring - PlaidEasySoftware EngineerDesign a ChatGPT-like conversational assistant
This question evaluates a candidate's ability to design large-scale conversational AI systems, covering competencies in distributed system architecture, real-time streaming, stateful multi-turn session management, safety controls, and integration with external tools.
System DesignTechnical Screen - PlaidMediumMachine Learning EngineerDesign a Fraud Detection System
This question evaluates competency in ML system design for fraud detection within fintech data-connectivity platforms, testing real-time scoring, feature engineering (including relational/graph signals), label strategy, model training and serving, and operational concerns such as latency, privacy, monitoring, and robustness.
ML System DesignTechnical Screen - PlaidMediumSoftware EngineerDesign a coupon redemption system
This question evaluates proficiency in data structures and algorithms for building an in-memory service, including efficient lookup/update strategies, expiration handling, limit enforcement, idempotency, concurrency considerations, and time/space complexity reasoning.
Coding & AlgorithmsTechnical Screen - PlaidEasySoftware EngineerDesign a geo-distributed rate limiter
This question evaluates a candidate's competency in designing geo-distributed, globally consistent rate limiting systems that enforce per-API-key and additional constraints while balancing low-latency request paths and regional failure tolerance.
System DesignTechnical Screen - PlaidMediumSoftware EngineerDesign an Embeddable Pay by Bank Widget
Design a secure, embeddable Pay by Bank frontend widget and supporting backend infrastructure that enables direct bank checkout via an isolated iframe and asynchronous payment processing.
System DesignOnsiteSecurityWeb ArchitecturePayments - PlaidMediumSoftware EngineerExplain What You Seek and an Unexpected Project Outcome
Tests candidate self-awareness, career motivation, and adaptability when technical initiatives diverge from expectations due to real-world constraints.
Behavioral & LeadershipOnsiteBehavioralCareer GoalsAdaptability - PlaidMediumSoftware EngineerExplain project scope, timeline, and delegation
This question evaluates project management, technical ownership, estimation, risk management, delegation, and cross-team communication competencies within the Behavioral & Leadership domain for software engineers.
Behavioral & LeadershipTechnical Screen - PlaidMediumSoftware EngineerReason About Rate Limiting Under Memory and Throughput Pressure
Tests the candidate's ability to design a high-throughput, memory-bounded rate limiter using bucketed counters instead of unbounded timestamp queues, balancing concurrency, memory overhead, and precision.
Software Engineering FundamentalsOnsiteRate LimitingConcurrencyData Structures - PlaidEasySoftware EngineerResolve routing-number to bank mapping
This question evaluates a candidate's skills in data normalization, deduplication, aggregation, and conflict resolution across multiple JSON data sources, with emphasis on canonicalization of aliases and handling inconsistent mappings.
Coding & AlgorithmsTechnical Screen - PlaidMediumSoftware EngineerValidate Evaluation Chains and Resolve Boolean Outcomes
Implement a graph traversal to resolve Boolean evaluation chains with negation, detecting cycles, paths leading to cycles, and undefined references in linear time.
Coding & AlgorithmsTechnical ScreenGraphDFSCycle Detection - PlaidMediumSoftware EngineerValidate and Resolve Chained Decision Rules
Determine if all rules in a chained decision rule set resolve to a terminal 'pass' outcome without cycles or missing references.
Coding & AlgorithmsTechnical ScreenGraphDFSCycle Detection - PlaystationMediumData ScientistDesign Experiments Under Network Interference
This problem tests your understanding of causal inference in networked environments, focusing on how to detect and mitigate bias when treatment effects spill over between connected users in a social gaming platform.
Analytics & ExperimentationTechnical ScreenCausal InferenceA/B TestingNetwork Science - PlaystationEasySoftware EngineerGroom a Ticket to Replace a Store's 12+ Age Rating with a Pending Rating
A ten-minute ticket-grooming exercise in which a software engineer and a product manager groom a ticket that removes a game store's 12+ age rating and adds a Pending rating. It tests asking scope-changing questions, splitting the work into parallel tasks with clear dependencies, and giving a reasoned ETA.
Software Engineering FundamentalsTechnical Screen - PlaystationEasySoftware EngineerMost Complex Project, Ideal Work Environment, Job Values and Hobbies
Four behavioral questions from a software engineer screen: the most complex thing you have worked on, the environment in which you thrive, what you value in a job, and what you do for fun. It tests ownership, self-awareness and team fit, and the ability to give concise, specific answers backed by real examples.
Behavioral & LeadershipTechnical Screen
Pinterest
Plaid
Playstation