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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 1–30 of 253 results
- AdobeMediumMachine Learning EngineerDetermine if a multiple-sum subarray exists
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Determine if a multiple-sum subarray exists states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsOnsite - AdobeMediumMachine Learning EngineerImplement K-means clustering from scratch
This problem tests your understanding of the K-means clustering algorithm, specifically the iterative process of centroid initialization, assignment, and update steps.
Coding & AlgorithmsTechnical ScreenK-meansClusteringUnsupervised Learning - AirbnbMediumMachine Learning EngineerMinimize exact layover bookings
This problem tests your ability to use dynamic programming to determine if a specific target sum can be achieved using a subset of given item values and how to find the minimum subset size that hits that target.
Coding & AlgorithmsOnsiteDynamic ProgrammingOptimizationAlgorithms - AirbnbMediumMachine Learning EngineerMinimum Canisters to Top Up an Exact Target
Tests dynamic programming for the unbounded knapsack/coin change problem, focusing on finding the minimum number of canisters to reach an exact volume and reconstructing the optimal selection.
Coding & AlgorithmsTechnical Screendynamic-programmingknapsackarrays - AirbnbMediumMachine Learning EngineerRedact Document Phrases with Simultaneous Replacement
Redact document phrases with a replacement map, whole-word matching, longest-match overlap rules, and one-pass replacement of original text.
Coding & AlgorithmsOnsite - AirbnbMediumMachine Learning EngineerSolve Decimal Coin Change
This question evaluates proficiency in dynamic programming for coin-change problems and competency in numerical precision and safe handling of decimal monetary values in algorithmic implementations.
Coding & AlgorithmsOnsite - AnthropicMediumMachine Learning EngineerConvert Samples into Event Intervals
This problem tests your ability to process sequential data, apply run-length encoding concepts, and implement filtering logic based on temporal constraints.
Coding & AlgorithmsTechnical ScreenArrayIntervalsData Processing - AnthropicMediumMachine Learning EngineerConvert State Stream to Events
This question tests the ability to process a stream of state changes, group consecutive identical values into distinct event intervals, and filter these events based on duration.
Coding & AlgorithmsOnsiteArraysData ProcessingAlgorithms - AnthropicMediumMachine Learning EngineerConvert stack samples to execution trace
This question evaluates understanding of sampled stack traces, event reconstruction, handling ambiguous or incomplete profiling data, and algorithmic reasoning about correctness and time/space complexity.
Coding & AlgorithmsTechnical Screen - AnthropicHardMachine Learning EngineerImplement a Simplified DNS Resolver
Implement an in-memory DNS resolver supporting A and CNAME record lookups, domain name normalization, TTL expiration, and CNAME alias chain cycle detection.
Coding & AlgorithmsOnline AssessmentHash TableGraphDesign - AnthropicMediumMachine Learning EngineerImplement a web crawler using a provided API
This problem tests your ability to design a multi-threaded web crawler that efficiently traverses a site while respecting domain constraints and avoiding redundant work.
Coding & AlgorithmsOnsiteConcurrencyGraph TraversalBFS - AnthropicMediumMachine Learning EngineerImplement an extensible prefix tree
This question evaluates the ability to design and implement an extensible prefix tree (trie), covering competencies in Unicode-aware string handling, memory and time optimization, concurrency or thread-safety considerations, and support for operations like insert, search, startsWith, countPrefix and erase.
Coding & AlgorithmsOnsite - AnthropicMediumMachine Learning EngineerImplement cluster status tracker
This question evaluates a candidate's competence in data structures and algorithms for time-ordered state tracking, time-series indexing, conflict resolution (last-write-wins), memory-efficient storage, and concurrent system behavior under high update rates.
Coding & AlgorithmsTechnical Screen - AppleMediumMachine Learning EngineerDebug a PyTorch U-Net shape mismatch
This question tests your ability to calculate the output dimensions of convolutional layers in a U-Net architecture and resolve shape mismatches caused by cropping or padding requirements during feature map concatenation.
Coding & AlgorithmsTechnical ScreenPyTorchComputer VisionU-Net - AppleMediumMachine Learning EngineerFind Minimum Processing Rate
This problem tests your ability to use binary search on a search space to find an optimal minimum processing rate that satisfies a global deadline constraint.
Coding & AlgorithmsTechnical ScreenBinary SearchGreedyOptimization - AppleMediumMachine Learning EngineerImplement Kubernetes Service Dependency Queries
This question evaluates proficiency with data structures and algorithms for service inventory operations, including deterministic filtering, attribute matching, graph traversal for transitive dependency resolution, and status propagation across service graphs.
Coding & AlgorithmsOnsite - AppleMediumMachine Learning EngineerImplement TF-IDF scoring for documents
This question evaluates understanding of information retrieval and text representation concepts—specifically TF–IDF weighting, tokenization, term frequency and document frequency—and measures competency in implementing an efficient scoring and ranking algorithm.
Coding & AlgorithmsTechnical Screen - AppleMediumMachine Learning EngineerImplement bag-of-words similarity search from scratch
This question evaluates knowledge and implementation skills in text processing, vector-space models, and information retrieval, covering tokenization, term-frequency and TF–IDF weighting, cosine similarity, and ranking for similarity search within the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen - AppleMediumMachine Learning EngineerImplement permutations and image retrieval
This question evaluates algorithmic implementation and computational thinking across combinatorics, image processing, and vector similarity—specifically testing permutation generation, 2D convolution with explicit boundary handling, and nearest-neighbor retrieval for image embeddings.
Coding & AlgorithmsOnsite - AppleMediumMachine Learning EngineerRotate a Matrix In Place
This question evaluates proficiency in in-place matrix and array manipulation, spatial data transformation, and reasoning about time and space complexity.
Coding & AlgorithmsTechnical Screen - AppleMediumMachine Learning EngineerSolve stock and banana problems
This question evaluates algorithmic problem-solving skills related to array processing, optimization under constraints, and reasoning about performance trade-offs by presenting a maximum single-transaction stock profit problem and a minimum banana-eating speed problem.
Coding & AlgorithmsOnsite - AppleMediumMachine Learning EngineerWrite a generator for substring pattern matches
This question evaluates understanding of string pattern matching and generator/iterator design, testing skills in handling overlapping matches, streaming output, and worst-case time complexity considerations.
Coding & AlgorithmsTechnical Screen - Applied IntuitionMediumMachine Learning EngineerImplement a Fixed-Capacity Deque
This question evaluates proficiency with double-ended queue semantics, fixed-capacity data structure design, constant-time (O(1)) operations, and correct handling of boundary conditions and wraparound.
Coding & AlgorithmsTechnical Screen - Applied IntuitionHardMachine Learning EngineerValidate Nested Configuration Objects
This question evaluates schema validation skills including recursive data structures, primitive and composite type checking, and structured error reporting for configuration objects, categorized under Coding & Algorithms for a Machine Learning Engineer role and focused on practical implementation.
Coding & AlgorithmsTechnical Screen - AtlassianMediumMachine Learning EngineerAssign bookings to minimum tennis courts
This problem tests your ability to manage overlapping time intervals using a greedy approach, specifically requiring the calculation of the maximum number of concurrent bookings to determine the minimum resource count.
Coding & AlgorithmsOnsiteGreedySortingIntervals - AtlassianHardMachine Learning EngineerCompute a moving average on a stream
This problem tests your ability to maintain a running average over a sliding window of size K in a high-throughput streaming environment while managing numerical precision and memory efficiency.
Coding & AlgorithmsOnsiteAlgorithmsData StructuresStreaming - AtlassianMediumMachine Learning EngineerCompute inverse-depth weighted sum of a nested list
This problem tests your ability to traverse nested list structures using recursion or iterative stacks and compute a value based on the nesting depth of individual elements.
Coding & AlgorithmsOnsiteRecursionTreesData Structures - AtlassianMediumMachine Learning EngineerCompute moving average over last N stream
This question evaluates understanding of streaming algorithms and sliding-window aggregation within the Coding & Algorithms domain, focusing on incremental computation, state management, and numerical stability when computing moving averages.
Coding & AlgorithmsOnsite - AtlassianMediumMachine Learning EngineerDesign O(1) cache and moving average
This problem tests your ability to maintain constant-time complexity for both cache management and sliding-window statistics by using a combination of a doubly-linked list and hash maps.
Coding & AlgorithmsOnsiteLRU CacheData StructuresSliding Window - AtlassianMediumMachine Learning EngineerFind LCA in a tree and extend to a DAG
This problem tests your understanding of tree traversal, graph theory, and how to generalize path-finding algorithms from trees to directed acyclic graphs (DAGs).
Coding & AlgorithmsOnsiteGraphsLCATrees
Adobe
Airbnb
Anthropic
Apple
Applied Intuition
Atlassian