practice a little every day, paws crossed ♡
Machine Learning Engineer 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 541–570 of 782 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 - 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 - 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 - 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 - Point72MediumMachine Learning EngineerDesign Features for Residual Volatility
This problem tests the ability to decompose financial asset returns into systematic and idiosyncratic components and design features to capture residual volatility.
Machine LearningTechnical ScreenTime-SeriesFinanceFeature Engineering - Point72MediumMachine Learning EngineerFind the Smallest String After One Decrement
This question evaluates string manipulation, lexicographic ordering, and reasoning about local character transformations including wrap-around behavior.
Coding & AlgorithmsTechnical Screen - RbcroyalbankMediumMachine Learning EngineerNavigate Conflict, Compromise, and a Revealed Weakness
This set of behavioral prompts evaluates a candidate's ability to navigate professional friction, demonstrate self-awareness regarding technical limitations, and exercise judgment in collaborative software development.
Behavioral & LeadershipTechnical ScreenBehavioralConflict ResolutionLeadership - RbcroyalbankMediumMachine Learning EngineerProcess Operations for an In-Memory Key-Value Store
This problem tests proficiency with hash map operations and handling data retrieval edge cases within an in-memory data store.
Coding & AlgorithmsTechnical ScreenHash MapData StructuresAlgorithms - RedditMediumMachine Learning EngineerAnalyze CTR Data and Train Model
This problem tests the end-to-end workflow of building a CTR prediction model, focusing on feature engineering for high-cardinality categorical data and handling temporal leakage.
Machine LearningOnsiteFeature EngineeringCTR PredictionData Leakage - RedditMediumMachine Learning EngineerBuild and evaluate click prediction models
This question evaluates skills in supervised probabilistic modeling for click-through rate prediction, including model selection, calibration, evaluation metric choice, cross-validation, hyperparameter tuning, and production concerns like serving and monitoring.
Machine LearningTechnical Screen - RedditMediumMachine Learning EngineerDescribe a failure and a success
This question evaluates ownership, communication, accountability, and impact assessment within engineering and machine learning contexts, focusing on incident management, model launches, delivery outcomes, and collaboration.
Behavioral & LeadershipOnsite - RedditMediumMachine Learning EngineerDesign Comment Prediction Ranking System
This question assesses the ability to design an end-to-end ML pipeline for ranking comments by predicted user engagement probability, balancing accuracy, latency, and system scalability.
ML System DesignTechnical ScreenRankingRecommendation SystemsFeature Engineering - RedditMediumMachine Learning EngineerDesign a Comment-Likelihood Prediction System with a Focus on Feature and Model Serving
Design a machine-learning system that predicts how likely a user is to comment on a post, covering label definition, features and model choice, with most of the depth on feature serving and model serving. Tests online and offline feature consistency, feature freshness, latency budgets and safe model deployment.
ML System DesignOnsite - RedditEasyMachine Learning EngineerDesign a Tennis Scoring System
This problem tests your ability to model state transitions, encapsulate logic using object-oriented principles, and implement conditional rule-based scoring in a competitive game.
Software Engineering FundamentalsTechnical ScreenObject-Oriented DesignState MachineLogic - RedditMediumMachine Learning EngineerDesign a video recommendation system
This question evaluates ML system design competencies for a Machine Learning Engineer, covering infrastructure architecture, logging and observability, feature pipelines, model training/evaluation, serving reliability, and privacy-aware data practices within the ML System Design domain.
ML System DesignOnsite - RedditHardMachine Learning EngineerDesign comment ranking
This problem evaluates your ability to design a scalable comment ranking system that balances engagement, relevance, and safety, while addressing the challenges of low-latency inference and data freshness.
ML System DesignOnsiteRankingInformation RetrievalRecommender Systems - RedditMediumMachine Learning EngineerExclude Cat- or Dog-Related Comments and All Their Replies by Reader Mode
Given discussion comments that form reply trees, each flagged as being about cats, dogs, both or neither, return every comment a cat person or a dog person should not see, where hiding a comment also hides all of its replies. Tests reasoning over tree structure, edge cases such as missing parents, and complexity analysis.
Coding & AlgorithmsOnsite - RedditHardMachine Learning EngineerExplain and Reduce Position Bias in Ranking
Assess understanding of position bias in click-based ranking systems, including formalizing the examination hypothesis, estimating observation propensities, training with Inverse Propensity Scoring (IPS), and designing counterfactual evaluation metrics.
Machine LearningTechnical ScreenRankingRecommendationPosition Bias - RedditMediumMachine Learning EngineerImplement a simplified memcached server
This problem tests your ability to design a thread-safe, in-memory key-value store and implement basic command parsing for an asynchronous network service.
Coding & AlgorithmsTechnical ScreenConcurrencyData StructuresCaching - RedditHardMachine Learning EngineerImprove Reddit onboarding
This question evaluates product sense, analytical reasoning, experiment design, and cross-functional leadership in the context of improving first-time user onboarding and activation on a community platform, testing competencies in user research, metric definition, prioritization, and validation.
Behavioral & LeadershipOnsite - RedditMediumMachine Learning EngineerModel y from x and interpret distributions
This question evaluates modeling judgment in machine learning, covering problem framing (regression versus classification), baseline model and metric selection, interpretation of feature or class distribution differences, and cold-start strategies for users, items, and regions.
Machine LearningOnsite - RedditHardMachine Learning EngineerSolve palindrome and list tasks
This problem tests your ability to manipulate string prefixes to satisfy palindromic properties and your skill in performing in-place linked list reordering based on node index parity.
Coding & AlgorithmsOnsiteStringLinked ListTwo Pointers - RipplingMediumMachine Learning EngineerImplement stack and interval algorithms with tests
This question evaluates implementation-level competencies with fundamental data structures and algorithms—stack-based bracket validation, interval merging with open/closed endpoint semantics, and arithmetic expression evaluation using stacks—while also measuring the ability to design comprehensive unit tests; category: Coding & Algorithms for a Machine Learning Engineer role. It is commonly asked to gauge practical coding ability, correctness under tricky edge cases and input semantics, and test-coverage awareness, representing a practical application-level assessment that also requires conceptual reasoning about invariants and boundary behavior.
Coding & AlgorithmsOnsite - Ro.CoMediumMachine Learning EngineerDebug an inaccurate patient-message triage classifier service and write up fixes
A one-hour take-home for a senior applied AI engineering role: debug a telehealth service that sorts patient messages into care categories with an urgency and a confidence score, decide when to call an LLM or send a message to manual review, and write up bugs, priorities and trade-offs. It tests debugging, safety judgment and ML evaluation.
Machine LearningOnline Assessment - RobloxMediumMachine Learning EngineerDesign a Game Recommendation System
This problem tests your ability to design a multi-stage recommendation architecture tailored to a gaming platform, focusing on user-specific constraints like age-appropriateness and the challenges of the long-tail game distribution.
ML System DesignOnsiteRecommendation SystemsSystem DesignRanking - RobloxMediumMachine Learning EngineerDesign a game genre classifier
This question assesses the ability to design an end-to-end multi-modal machine learning system for classifying user-generated game content based on diverse input features and real-time serving requirements.
ML System DesignOnsiteMulti-modalNLPComputer Vision - RobloxHardMachine Learning EngineerDesign a real-time game recommendation system
Design a real-time game recommendation system evaluates ML product requirements, data/labeling, modeling, serving architecture, evaluation, monitoring, and trade-offs in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
ML System DesignTechnical Screen - RobloxEasyMachine Learning EngineerExtend counter to per-client rate limiting
This question evaluates competency in designing per-client, time-windowed rate limiting using efficient data structures for time-based eviction and counting within the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen - RobloxMediumMachine Learning EngineerFind Windows Containing a Target
This problem tests your ability to efficiently filter and identify intervals within a collection that satisfy specific containment constraints using two-pointer or sliding window techniques.
Coding & AlgorithmsOnsiteArraysFilteringIntervals - RobloxMediumMachine Learning EngineerFind target-heavy sliding windows
This question tests the ability to implement an efficient sliding window algorithm to analyze frequency-based patterns within a data stream or array.
Coding & AlgorithmsOnsiteSliding WindowAlgorithmsArray
Pinterest
Plaid
Point72
Reddit
Rippling
Roblox