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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 61–90 of 253 results
- GleanMediumMachine Learning EngineerDetermine Reachability in Train Schedule
Solve train-schedule reachability with waiting and transfers using time-respecting graph search. The answer models earliest station arrival, preprocesses station visits, handles forward-only train routes, and explains transfer edge cases and complexity.
Coding & AlgorithmsTechnical Screen - GleanMediumMachine Learning EngineerFind Earliest Train Route
This question evaluates a candidate's ability to model and search time-dependent transit networks, combining temporal graph reasoning, state-space search, and path reconstruction for itinerary reporting.
Coding & AlgorithmsOnsite - GleanMediumMachine Learning EngineerImplement Rate-Limited Wikipedia Crawler
This question evaluates a candidate's ability to implement a rate-limited web crawler, testing skills in crawl frontier management, prioritization by page-title initial, deduplication, rate limiting, and robust error handling.
Coding & AlgorithmsOnsite - Goldman SachsHardMachine Learning EngineerComplete decision tree and gradient descent functions
This question evaluates implementation skills in supervised machine learning and numerical optimization, specifically computing Gini impurity and selecting optimal binary splits for a decision tree alongside deriving and applying a single-step gradient descent update for linear regression.
Coding & AlgorithmsOnline Assessment - GoogleMediumMachine Learning EngineerCompute sum over consecutive-step subarrays
This problem tests your ability to identify contiguous subarrays that follow an arithmetic progression with a common difference of 1 (consecutive steps) and calculate the sum of elements within these subarrays efficiently.
Coding & AlgorithmsOnsiteArraysMathSliding Window - GoogleHardMachine Learning EngineerConstruct connected crop layout and safe paths
This problem tests your ability to design a constructive grid layout that satisfies connectivity and size constraints, followed by pathfinding through dynamic or constrained environments.
Coding & AlgorithmsTechnical ScreenBacktrackingGraph TheoryBFS - GoogleMediumMachine Learning EngineerImplement a Transformer Block with SwiGLU
This question evaluates implementation and reasoning skills for Transformer internals, testing competency in multi-head self-attention, SwiGLU gated feed-forward layers, residual connections, and layer normalization within the Machine Learning / deep learning domain.
Coding & AlgorithmsTechnical Screen - GoogleMediumMachine Learning EngineerImplement substring search and weighted sampling
This question tests the ability to implement a fast substring matching algorithm and a data structure that supports weighted random sampling from a dynamic collection of items.
Coding & AlgorithmsTechnical ScreenString MatchingKMPProbability - GoogleMediumMachine Learning EngineerMinimize Fence Painting Operations
This problem tests your ability to use a greedy approach or dynamic programming to find the minimum number of strokes required to paint a fence of varying heights.
Coding & AlgorithmsTechnical ScreenGreedyStackArrays - GoogleHardMachine Learning EngineerSolve several streaming, DAG, and DP tasks
Implement an ML pipeline optimization engine that calculates critical path latency and peak parallelism for a task DAG, and optimizes streaming checkpoint placement under sliding-window constraints using dynamic programming.
Coding & AlgorithmsOnsiteDAGDynamic ProgrammingSliding Window - HackerRankMediumMachine Learning EngineerCount Good Subsequences With Equal Character Frequencies
Practice a combinatorics coding problem that counts good subsequences where every selected character has the same frequency. The prompt targets frequency counting, combinations, modular arithmetic, and grouping subsequences by common selected count.
Coding & AlgorithmsOnline Assessment - HarveyMediumMachine Learning EngineerImplement a Spreadsheet With Formulas
This problem tests your ability to model cell dependencies using a directed graph, handle topological sorting for re-evaluation, and identify circular references.
Coding & AlgorithmsTechnical ScreenGraphsRecursionDFS - Hudson River TradingEasyMachine Learning EngineerCount People Reaching the Boundary
This question evaluates algorithmic simulation and event-driven modeling skills, specifically handling discrete versus continuous time, visibility constraints relative to a stationary watcher that changes facing direction, and boundary conditions for state transitions.
Coding & AlgorithmsOnsite - InstacartHardMachine Learning EngineerSolve Two Sorted-Array Tasks
This problem tests your ability to efficiently merge and find elements in sorted arrays, focusing on optimal time complexity and edge case handling.
Coding & AlgorithmsTechnical ScreenArraysBinary SearchTwo Pointers - J.P. MorganMediumMachine Learning EngineerReturn Every Index Pair Whose Values Sum to a Target
This problem tests your ability to handle frequency counts and index tracking using hash maps to identify all possible index pairs that sum to a specific target, particularly in the presence of duplicate values.
Coding & AlgorithmsTechnical ScreenHash MapArraysAlgorithms - Jane StreetMediumMachine Learning EngineerBoard Simulation: Bottom-Insert Pieces with Uniform Row and Column Detection
This question evaluates the ability to simulate a 2-D game board and maintain dynamic state invariants, testing array manipulation, state-tracking, and detection of uniform rows and columns under bottom-insert semantics.
Coding & AlgorithmsTechnical Screen - Jane StreetMediumMachine Learning EngineerCode Editor with Block Shrink and Expand (Code Folding)
This question evaluates a candidate's ability to model and manipulate indentation-based hierarchical structures, maintain nested visibility state for collapsed blocks, and map between original file lines and dynamic display numbering.
Coding & AlgorithmsTechnical Screen - Jane StreetMediumMachine Learning EngineerConnect-N on an Infinite Board with Gravity
This question evaluates implementation skills for efficient algorithms and data structures to manage a sparse, unbounded grid with gravity and to detect N-in-a-row runs both vertically and horizontally.
Coding & AlgorithmsTechnical Screen - Jane StreetEasyMachine Learning EngineerMarketplace Data Store: Order Matching and End-of-Day Reconciliation
This question evaluates understanding of stateful data structures, deterministic order-matching logic, and time-ordered reconciliation of transaction logs, focusing on correct handling of pricing, tie-breaking, and re-opened inventory.
Coding & AlgorithmsTechnical Screen - Jump TradingMediumMachine Learning EngineerSolve stock trading with pattern rules
This set of problems evaluates algorithmic skills in pattern recognition, state management, and sequence processing, specifically testing pattern-based decision rules on time-series stock data and iterative substring elimination in string processing within the Coding & Algorithms domain.
Coding & AlgorithmsOnline Assessment - Jump TradingMediumMachine Learning EngineerSolve stock-pattern trading and substring elimination
This question evaluates algorithmic skills in array pattern recognition and string processing, specifically detecting day-to-day sign patterns for simulated trading and repeated elimination of fixed two-character substrings; it belongs to the Coding & Algorithms domain for a Machine Learning Engineer position and targets practical application of linear-time, constant-extra-space techniques. It is commonly asked to evaluate efficient O(n) algorithm design, handling of stateful streaming simulations and in-place string reduction under tight time/space constraints, and correctness reasoning for edge cases.
Coding & AlgorithmsOnline Assessment - LinkedInEasyMachine Learning EngineerCompute point-to-segment minimum distance
This problem tests your ability to apply vector projections and geometric constraints to find the shortest distance from a point to a line segment in a 2D plane.
Coding & AlgorithmsTechnical ScreenGeometryVectorsMath - LinkedInMediumMachine Learning EngineerCompute total covered interval length
Compute total covered interval length evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen - LinkedInMediumMachine Learning EngineerFind shortest word transformation with caching
Find shortest word transformation with caching evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen - LinkedInMediumMachine Learning EngineerGenerate uniform 0–6 from biased coin
This question evaluates understanding of randomized algorithms, probability theory, and techniques for extracting uniform randomness from a biased source.
Coding & AlgorithmsOnsite - LinkedInMediumMachine Learning EngineerImplement K-Means and Explain Convergence
This problem tests the implementation of the K-means clustering algorithm from scratch, requiring an understanding of the iterative refinement process, distance metrics, and the underlying mathematical objective.
Coding & AlgorithmsTechnical ScreenClusteringUnsupervised LearningAlgorithms - LinkedInMediumMachine Learning EngineerImplement alert queries and spike detection
This problem tests your ability to process a stream of events with time-based constraints, requiring an efficient sliding-window approach and the use of monotonic data structures for spike detection.
Coding & AlgorithmsOnsiteSliding WindowData StructuresStreaming - LinkedInMediumMachine Learning EngineerSample index from probability distribution
This question tests the ability to implement a weighted random sampling algorithm efficiently using prefix sums and binary search to achieve sub-linear query time.
Coding & AlgorithmsOnsiteAlgorithmsProbabilityBinary Search - LinkedInMediumMachine Learning EngineerSample uniformly from a circle’s area
This question evaluates understanding of continuous probability distributions and geometric random sampling, testing whether a candidate recognizes how area-weighted uniformity differs from naive radial choices.
Coding & AlgorithmsOnsite - LinkedInMediumMachine Learning EngineerSort the values of a quadratic function applied to a sorted array in linear time
Given an integer array sorted in ascending order and the coefficients of a quadratic function, apply the function to every element and return the results in sorted order in linear time. Tests reasoning about the shape of a parabola, handling of positive, negative and zero leading coefficients, and duplicate values.
Coding & AlgorithmsTechnical Screen
Glean
Goldman Sachs
Google
Harvey
Hudson River Trading
Instacart
J.P. Morgan
Jane Street
LinkedIn