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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.
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Showing 511–540 of 782 results
- 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 - PerplexityMediumMachine Learning EngineerTrain and improve a scikit-learn binary classifier
This problem tests your proficiency in the scikit-learn workflow, specifically focusing on data preprocessing, addressing class imbalance in imbalanced datasets, and selecting appropriate metrics beyond accuracy.
Machine LearningTechnical Screenscikit-learnImbalanced DataModel Evaluation - PinterestHardMachine Learning EngineerAnswer core ML fundamentals questions
This question evaluates a candidate's mastery of core Machine Learning fundamentals, including classification metrics (precision and recall) with confusion-matrix interpretation, gradient concepts for optimization, ensemble learning tradeoffs, and the mechanics of a neural network forward pass.
Machine LearningOnline Assessment - PinterestHardMachine Learning EngineerBias-Variance Tradeoff and Vanishing Gradients in Feedforward Networks
Tests theoretical and mathematical understanding of the bias-variance decomposition and the vanishing-gradient phenomenon during backpropagation in deep feedforward architectures.
Machine LearningTechnical ScreenDeep LearningBackpropagationModel Generalization - 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 Hierarchical Permission Checks
This question evaluates understanding of hierarchical access control, tree data structures, and permission inheritance, testing competencies in data modeling and algorithmic reasoning.
Coding & AlgorithmsTechnical Screen - 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 ads system to improve CTR
This question evaluates machine learning system design competency for improving ad click-through rate, testing understanding of metrics, end-to-end architecture, training data and embeddings, and operational issues like cold start, bias and delayed feedback within advertising and recommender domains.
ML System DesignTechnical Screen - 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 EngineerExplain bias–variance, overfitting, and vanishing gradients
This question tests the conceptual understanding of the bias-variance tradeoff, methods for diagnosing and preventing overfitting, and the theoretical causes and architectural solutions for vanishing gradients in deep learning.
Machine LearningTechnical ScreenDeep LearningBias-Variance TradeoffRegularization - PinterestEasyMachine Learning EngineerExplain learning-rate fluctuation and vanishing gradients
This question evaluates a candidate's understanding of optimization dynamics (effects of learning rate on training stability) and backpropagation-related issues (vanishing gradients) in deep neural networks, assessing competencies in training behavior and gradient propagation within the Machine Learning domain.
Machine LearningTechnical Screen - PinterestHardMachine Learning EngineerExplain overfitting and how to prevent it
This question evaluates understanding of overfitting, the relationship between training and validation performance and generalization, and knowledge of regularization concepts including differences between L1 and L2 penalties.
Machine LearningTechnical Screen - PinterestHardMachine Learning EngineerExplain overfitting, underfitting, and regularization
This question tests the conceptual understanding of the bias-variance tradeoff and the practical application of regularization to balance model complexity and generalization error.
Machine LearningTechnical ScreenBias-VarianceRegularizationGeneralization - 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 EngineerGenerate all hyperparameter combinations
This problem tests your ability to generate the Cartesian product of multiple lists, a fundamental task in grid search for hyperparameter tuning.
Coding & AlgorithmsTechnical ScreenCombinatoricsRecursionIteration - 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 Naive Bayes classifier from scratch
This question evaluates understanding of probabilistic classification, specifically competence in estimating class priors, feature likelihood parameters, and computing posterior scores for Naive Bayes variants.
Machine LearningOnline Assessment - PinterestMediumMachine Learning EngineerImplement a Sparse Matrix Class
Design and implement a memory-efficient sparse matrix class supporting entry retrieval, updates, addition, and matrix multiplication.
Coding & AlgorithmsTechnical Screensparse-matrixhash-tablelinear-algebra - PinterestHardMachine Learning EngineerImplement a Stateful Search Autocomplete Session
Design an interactive autocomplete system that tracks query frequencies, returns the top 3 ranking prefix matches per keystroke, and commits completed queries to dynamic history.
Coding & AlgorithmsTechnical ScreenTrieHash TableDesign - PinterestHardMachine Learning EngineerImplement bagging with decision trees
This question evaluates a candidate's competency in ensemble learning and practical implementation skills, including bootstrap sampling, decision tree base learners, aggregation via majority voting with tie-breaking, and managing data using pure Python lists and standard library routines.
Machine LearningOnline Assessment - PinterestEasyMachine Learning EngineerImplement string-based rounding without floats
This question evaluates proficiency in string-based numeric processing, arbitrary-precision arithmetic concepts, precise rounding rules including deterministic tie-breaking, and handling of sign and decimal edge cases, and falls under the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen - 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 - PinterestHardMachine Learning EngineerPrevent Vanishing Gradients in Deep Networks
Tests a candidate's mathematical understanding of the vanishing gradient problem in deep neural networks and their ability to evaluate architectural mitigations including weight initialization, activation functions, residual connections, and normalization layers.
Machine LearningTechnical ScreenDeep LearningOptimizationNeural Networks - 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 - PinterestHardMachine Learning EngineerSolve a 9x9 Sudoku puzzle
This question evaluates algorithmic problem-solving skills focused on constraint satisfaction, state-space search, and implementation correctness for combinatorial puzzles.
Coding & AlgorithmsTechnical Screen - 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
PayPal
Perplexity
Pinterest