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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
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Showing 241–270 of 351 results
- OpenAIMediumMachine Learning EngineerTrack Expiring GPU Credits
Design an in-memory credit ledger to track expiring GPU compute credits, support priority consumption, and manage resource debt.
Coding & AlgorithmsOnsiteHeapDesignGreedy - OtherMediumMachine Learning EngineerImplement Linear Regression Training
This question evaluates understanding of linear regression, mean squared error loss, gradient computation, parameter updates, and proficiency with vectorized numerical operations used in batch gradient descent.
Coding & AlgorithmsOnsite - PayPalHardMachine Learning EngineerDesign a traditional fraud detection system
This question evaluates a Machine Learning Engineer's competency in end-to-end ML system design for real-time payments fraud detection, including labeling under delayed confirmations, handling extreme class imbalance and sampling, feature engineering across behavioral, graph, device and merchant signals, model selection for latency and scale, and production scoring and monitoring architecture. It is commonly asked in the ML System Design category to assess how an engineer balances low-latency decision-making with delayed sparse labels, calibration and threshold trade-offs, operational scalability and resiliency, and drift/adversarial detection, testing both conceptual understanding and practical application.
ML System DesignOnsite - PayPalMediumMachine Learning EngineerMaximize ones with limited flips
This question evaluates proficiency with array algorithms, particularly sliding-window and two-pointer reasoning, complexity analysis, and the ability to adapt solutions for streaming data.
Coding & AlgorithmsOnsite - PayPalMediumMachine Learning EngineerSearch a word in a grid
This question evaluates proficiency in grid traversal and stateful search techniques such as depth-first search and backtracking, including visited-state management and pruning strategies within the Coding & Algorithms domain.
Coding & AlgorithmsOnsite - PinterestMediumMachine Learning EngineerDescribe a Failure or Mistake and Its Lasting Lesson
This question assesses your ability to reflect on professional shortcomings, demonstrate accountability, and translate failure into actionable growth for both yourself and your team.
Behavioral & LeadershipOnsiteBehavioralAccountabilityConflict Resolution - PinterestMediumMachine Learning EngineerDesign Detection Systems for Risk and Safety
This question tests the ability to design an end-to-end classification system for detecting harmful content (e.g., spam or toxic images) while balancing precision and recall at scale.
ML System DesignOnsiteComputer VisionNLPContent Moderation - PinterestMediumMachine Learning EngineerDesign User and Item Embeddings from Long Histories
Design an end-to-end candidate retrieval system using user and visual-item embeddings capable of processing ultra-long user histories (up to 160,000 interactions) while handling real-time freshness, cold-start items, and privacy constraints.
ML System DesignOnsiteRecommendation SystemsVector EmbeddingsCandidate Retrieval - PinterestHardMachine Learning EngineerDesign a real-time home feed ranker
This problem evaluates your ability to design a multi-stage recommendation architecture capable of integrating real-time user signals, managing feature latency, and balancing ranking accuracy with system throughput.
ML System DesignOnsiteSystem DesignRecommendation SystemsReal-time - PinterestHardMachine Learning EngineerDesign an unsafe content detection system
This problem evaluates your ability to design a scalable, multimodal machine learning pipeline for detecting policy-violating content on a large-scale visual discovery platform.
ML System DesignOnsiteMultimodal LearningReal-time InferenceContent Moderation - PinterestMediumMachine Learning EngineerDesign notification and feed recommenders
This question tests the ability to design a dual-purpose recommendation architecture capable of handling real-time push notifications and personalized feed updates at scale.
ML System DesignOnsiteRecommender SystemsRankingScalability - PinterestMediumMachine Learning EngineerFirst Word Matching Each Prefix Query
This problem tests your ability to efficiently query a list of strings to find the first occurrence that matches a given prefix, focusing on optimal space-time tradeoffs using tree-based or map-based indexing.
Coding & AlgorithmsOnsiteTrieHash MapString Processing - PinterestMediumMachine Learning EngineerHierarchical Access Control for an Advertising Platform
This problem tests graph traversal algorithms and efficient membership checking within a directed acyclic graph (DAG) representing hierarchical organizational permissions.
Coding & AlgorithmsOnsiteGraphsDAGBFS/DFS - PinterestHardMachine Learning EngineerImplement trie-based autocomplete
This problem tests your ability to implement a space-efficient Trie data structure capable of storing strings along with associated weights to return top-k suggestions for a given prefix.
Coding & AlgorithmsOnsiteTrieData StructuresStrings - PinterestMediumMachine Learning EngineerRank Newly Launched Ads Under Cold Start
Design a machine learning system to rank and explore cold-start ads launched within the past seven days, balancing marketplace revenue, user engagement, and advertiser budget delivery.
ML System DesignOnsiteml system designcold startad tech - PinterestMediumMachine Learning EngineerSolve Expression and Tree-List Problems
This problem tests recursive backtracking for expression generation and pointer manipulation for in-place tree-to-linked-list conversion.
Coding & AlgorithmsOnsiteBacktrackingTreesLinked Lists - PinterestMediumMachine Learning EngineerSolve five hard algorithm problems
This problem tests your ability to optimize range-based operations using a difference array or prefix sum strategy and demonstrates your skill in balancing computational efficiency with memory constraints.
Coding & AlgorithmsOnsiteArraysPrefix SumDifference Array - 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 - 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 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 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 - 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 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
OpenAI
PayPal
Pinterest
Plaid
Reddit
Rippling