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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
- Questions
- 546
- Companies
- 11
- Topics
- 8
- Languages
Showing 1–13 of 13 results
- AdyenEasyMachine Learning EngineerBuild a Payment Fraud Detection Model
Tests practical machine learning design for payment fraud detection, covering data preprocessing, temporal validation splits, class imbalance handling, and metric selection.
Machine LearningHR ScreenFraud DetectionClassificationFeature Engineering - AnthropicMediumMachine Learning EngineerDesign a Double Descent Experiment
Tests your ability to design a controlled synthetic experiment demonstrating double descent, explain the mathematical causes of test error divergence near the interpolation threshold, and analyze the interplay between noise, conditioning, and regularization.
Machine LearningHR Screendouble-descentgeneralizationlinear-models - AnthropicMediumMachine Learning EngineerWalk Through Your Work Background and Explain Your Concerns About AI Safety
A recruiter screen question for a machine learning engineering role at an AI research company: give a concise overview of your work background, then explain the concerns you have about AI safety. It tests whether you can tell a focused career story and discuss safety risks with specific mechanisms, calibrated views and a link to the role.
Behavioral & LeadershipHR Screen - Capital OneMediumMachine Learning EngineerMaximize grid-path expression and count sawtooth subarrays
This multi-part question evaluates dynamic programming and state management for constrained grid traversal with left-to-right expression evaluation, alongside parity-based array analysis and combinatorial counting of contiguous subarrays.
Coding & AlgorithmsHR Screen - DandyMediumMachine Learning EngineerWhy do transformers struggle with long context?
This question evaluates understanding of transformer architectures, attention mechanisms, and scalability trade-offs, assessing competencies in computational complexity, memory usage, and system-level performance implications.
Machine LearningHR Screen - HubSpotMediumMachine Learning EngineerDiscuss compensation expectations and level
This question evaluates a candidate's ability to articulate compensation expectations, total rewards understanding (base, bonus, equity, sign-on) and flexibility, along with professional communication and self-awareness, and is categorized under Behavioral & Leadership and HR screening for compensation negotiation.
Behavioral & LeadershipHR Screen - MicrosoftMediumMachine Learning EngineerDesign a Retrieval-Grounded Local Sports News Recommender
This question tests the ability to design an end-to-end RAG system for news, focusing on temporal data relevance, hybrid retrieval strategies, and mitigation of LLM hallucinations.
ML System DesignHR ScreenRAGRecommendationSystem Design - MicrosoftMediumMachine Learning EngineerFind the Lowest Common Ancestor in a Binary Search Tree
This problem tests the ability to leverage the Binary Search Tree (BST) property to efficiently locate the Lowest Common Ancestor (LCA) of two nodes.
Coding & AlgorithmsHR ScreenBSTTreesRecursion - MicrosoftMediumMachine Learning EngineerFind the Lowest Common Ancestor in a Binary Tree
This problem tests tree traversal techniques and recursion logic to identify the deepest node that is an ancestor to two specified nodes in an arbitrary binary tree.
Coding & AlgorithmsHR ScreenTreesRecursionDFS - MicrosoftMediumMachine Learning EngineerImplement SFT Sample Packing
This problem tests your ability to efficiently pack variable-length sequences into fixed-length blocks for training, ensuring padding tokens do not influence the loss calculation.
Coding & AlgorithmsHR ScreenNLPData PreprocessingArrays - ShopifyMediumMachine Learning EngineerExplain motivation and role alignment
This question evaluates motivation, role alignment, and communication skills by asking a candidate to explain interest in the employer, educational choices, and career motivations as they relate to a Machine Learning Engineer role.
Behavioral & LeadershipHR Screen - ShopifyMediumMachine Learning EngineerExplain motivations, resume, and logistics
This question evaluates a candidate's ability to communicate career narrative, motivations, role-specific experiences, transitions, and logistical details such as work authorization and compensation, reflecting competencies in professional communication, self-awareness, and succinct storytelling for a Machine Learning Engineer role.
Behavioral & LeadershipHR Screen - UiPathMediumMachine Learning EngineerReduce overfitting and explain the mean squared error loss
A machine learning phone screen on how to diagnose and reduce overfitting, and on the mean squared error loss: its definition, what minimizing it estimates, its probabilistic interpretation, and when another loss works better. Tests fundamentals, mechanisms and trade-off reasoning.
Machine LearningHR Screen
Anthropic
Capital One
HubSpot
Microsoft
Shopify
UiPath