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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 91–120 of 253 results
- LinkedInHardMachine Learning EngineerSum Every Element of an N-Dimensional Array Readable Only by Index Lists
Compute the sum of all elements of an array with any number of dimensions when the array exposes only its dimension sizes and a get method that reads one element from a full list of indices. It tests systematic enumeration of every index combination and exact handling of sums beyond the 32-bit range.
Coding & AlgorithmsTechnical Screen - Luma AIMediumMachine Learning EngineerSolve Seven Python Image and Data Tasks
This problem tests foundational proficiency in NumPy array manipulation, mathematical function implementation, and geometric logic, which are essential for low-level image processing tasks.
Coding & AlgorithmsTechnical ScreenNumPyImage ProcessingNumerical Stability - MercorMediumMachine Learning EngineerCheck Whether Every Parcel Finds a Locker With Forward Overflow
Parcels arrive one at a time for a bank of numbered lockers, each requesting a preferred locker and overflowing to the next higher-numbered empty one if it's taken. Decide whether every parcel finds a locker. Tests precise rule-following and an efficient alternative to simulating forward scans one slot at a time.
Coding & AlgorithmsOnsiteunion-findsimulationarrays - MercorMediumMachine Learning EngineerImplement a Referral Network
Design and implement an in-memory referral network as a directed acyclic graph (DAG) supporting cycle-safe edge insertion, depth-bounded reachability queries, and expected reward computation under geometric decay.
Coding & AlgorithmsOnsiteGraph AlgorithmsDAGBFS - MetaMediumMachine Learning EngineerBuild Friend Recommendations
This problem tests your ability to manipulate graph-like data structures to perform neighbor analysis and efficient set operations to rank potential connections.
Coding & AlgorithmsTechnical ScreenGraphsHash MapsSocial Network Analysis - MetaHardMachine Learning EngineerBuild a Friend Recommender
This problem tests your ability to implement a graph-based recommendation algorithm using common neighbors and popularity constraints to rank potential connections.
Coding & AlgorithmsOnsiteGraphSortingRecommendation System - MetaMediumMachine Learning EngineerCheck diagonal and compute window statistics
This question evaluates understanding of array and matrix manipulation, sliding-window and streaming statistics, and appropriate data-structure choices for maintaining aggregates and order-statistics such as moving averages and sliding-window medians.
Coding & AlgorithmsTechnical Screen - MetaMediumMachine Learning EngineerCheck diagonal equality in a matrix
This question evaluates skill in matrix manipulation and algorithmic reasoning, specifically understanding diagonal traversal, equality checks, and handling boundary conditions such as empty matrices, single-row or single-column inputs, and negative values.
Coding & AlgorithmsTechnical Screen - MetaMediumMachine Learning EngineerCompute sliding-window medians
This question evaluates proficiency in designing and analyzing efficient sliding-window algorithms and data structures for computing running medians, including correct handling of duplicates, deletions, and the convention for defining the median when k is even.
Coding & AlgorithmsTechnical Screen - MetaMediumMachine Learning EngineerCompute the next lexicographic permutation
This problem tests your ability to manipulate array elements in-place to find the next lexicographically ordered sequence, focusing on understanding the properties of permutations.
Coding & AlgorithmsOnsiteArraysPermutationsTwo Pointers - MetaMediumMachine Learning EngineerDebug and optimize a card-drawing strategy
This problem tests your ability to simulate card-drawing probabilities, debug flawed logic in iterative selection strategies, and optimize performance for repeated simulations.
Coding & AlgorithmsOnsiteAlgorithmsSimulationProbability - MetaMediumMachine Learning EngineerDeep copy a linked list with random pointers
This problem tests your ability to manipulate complex pointer structures and maintain object identity across a deep copy operation in a non-linear linked list.
Coding & AlgorithmsTechnical ScreenLinked ListHash TablePointers - MetaHardMachine Learning EngineerFind Maximum Unique-Character Subset
This problem tests your ability to use bitmasking and backtracking with pruning to solve a variation of the maximum set packing problem under character constraints.
Coding & AlgorithmsOnsiteBitmaskingBacktrackingRecursion - MetaHardMachine Learning EngineerFind Words Containing Other Words
This problem tests your ability to efficiently identify all words in a list that contain at least one other word from the same list as a substring, utilizing optimized string processing or data structures like Tries.
Coding & AlgorithmsOnsiteStringsTrieOptimization - MetaMediumMachine Learning EngineerFind a String Containing Another
This question evaluates proficiency in string algorithms, substring search techniques, and algorithmic complexity analysis within the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen - MetaMediumMachine Learning EngineerFind kth smallest in sorted matrix
This question evaluates algorithmic problem-solving and data-structure knowledge, focusing on selection in a row-and-column-sorted matrix and the comparative use of min-heaps versus value-space binary search along with time/space complexity and edge-case analysis.
Coding & AlgorithmsOnsite - MetaMediumMachine Learning EngineerFind longest palindromic substring
This problem tests your ability to optimize string processing algorithms, specifically moving from a brute-force approach to an efficient expansion-based technique for identifying palindromic patterns.
Coding & AlgorithmsOnsiteStringsDynamic ProgrammingTwo Pointers - MetaMediumMachine Learning EngineerFind target using robot movement API
This question evaluates a candidate's ability to design exploration and state-space search strategies for a robot operating in an unknown, partially blocked 2D grid using a constrained movement and sensing API, testing competency in traversal algorithms, state management, and handling limited observability.
Coding & AlgorithmsOnsite - MetaMediumMachine Learning EngineerGenerate unique permutations with duplicates
This question evaluates a candidate's understanding of permutation generation and duplicate handling within algorithm design, testing combinatorial reasoning, correctness proofs, and time/space complexity analysis.
Coding & AlgorithmsOnsite - MetaMediumMachine Learning EngineerImplement BST Iterator and Ticket Queue
This problem tests your ability to implement an iterator for a Binary Search Tree (BST) using controlled traversal, and your skill in designing a priority-based queue that handles multi-criteria ordering.
Coding & AlgorithmsOnsiteTreesHeapsIterator - MetaMediumMachine Learning EngineerImplement LRU cache and copy random list
This problem tests your ability to handle complex pointer manipulation through linked-list deep copying and your proficiency in designing a thread-safe-capable cache using hash maps and doubly-linked lists.
Coding & AlgorithmsOnsiteLinked ListsHash MapsLRU Cache - MetaMediumMachine Learning EngineerImplement Sparse Matrix Operations
This question tests the ability to design an efficient data structure for sparse matrix storage and implement optimized multiplication between a sparse matrix and a dense vector.
Coding & AlgorithmsTechnical ScreenData StructuresLinear AlgebraOptimization - MetaMediumMachine Learning EngineerImplement exponentiation and fill grid distances
This problem tests proficiency in efficient modular exponentiation (binary exponentiation) and multi-source Breadth-First Search (BFS) for computing shortest distances in a grid.
Coding & AlgorithmsOnline AssessmentBFSModular ArithmeticDivide and Conquer - MetaMediumMachine Learning EngineerImplement exponentiation and link tree neighbors
This question evaluates numerical algorithm implementation and in-place tree traversal skills, specifically fast exponentiation with careful edge-case and precision handling and iterative linking of next pointers in a perfect binary tree.
Coding & AlgorithmsTechnical Screen - MetaMediumMachine Learning EngineerImplement weighted random sampling with preprocessing
This problem tests your ability to optimize weighted random selection using binary search on prefix sums, balancing preprocessing time against query latency.
Coding & AlgorithmsOnsiteProbabilityBinary SearchPrefix Sum - MetaMediumMachine Learning EngineerMaximize one stock trade profit
This question evaluates algorithm design skills for single-pass array processing, streaming data handling, and time/space complexity analysis within the Coding & Algorithms domain.
Coding & AlgorithmsOnsite - MetaMediumMachine Learning EngineerMaximize unique characters from a word list
This problem tests your ability to use recursion with backtracking or bitmasking to find the optimal subset of strings that maximize the total count of unique characters.
Coding & AlgorithmsOnsiteBacktrackingBitmaskingRecursion - MetaHardMachine Learning EngineerOptimize a Fifteen-Sum Card Strategy
This problem tests your ability to optimize a combinatorial search space through memoization and dynamic programming to determine the maximum win rate of a card-based strategy.
Coding & AlgorithmsOnsiteCombinatoricsProbabilityRecursion - MetaMediumMachine Learning EngineerOptimize repeated-value vectors and compute exclusive times
This question evaluates proficiency in data-structure and algorithmic concepts such as run-length encoding for compressed vectors and interval/nesting reasoning for computing exclusive execution times.
Coding & AlgorithmsTechnical Screen - MetaMediumMachine Learning EngineerOptimize ribbon piece length by binary search
This question evaluates understanding of binary-search-on-answer techniques and monotonic predicates, complexity analysis, and implementation-level handling of integer overflow and extreme edge cases in numeric partitioning, situated in the coding and algorithms domain and emphasizing practical implementation considerations rather than purely theoretical proofs. It is commonly asked because it reveals whether an interviewee can reason about monotonicity and design an O(n log max(lengths)) solution that remains robust under very large k, large element values, and potential integer overflow.
Coding & AlgorithmsOnsite
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Luma AI
Mercor
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