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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 211–240 of 253 results
- TeslaEasyMachine Learning EngineerImplement 2D convolution forward pass
This question evaluates understanding of 2D convolution mechanics and practical low-level tensor manipulation, including kernel shape handling, padding and stride effects, multi-channel input/output interactions, and optional bias integration.
Coding & AlgorithmsTechnical Screen - TeslaMediumMachine Learning EngineerImplement automatic braking logic in Python
This question evaluates understanding of kinematics, motion modeling, and numerical reasoning for safety-critical control logic, focusing on stopping-distance computation and the impact of reaction time on braking decisions.
Coding & AlgorithmsTechnical Screen - TikTokMediumMachine Learning EngineerCompute city skyline silhouette
Compute city skyline silhouette 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 - TikTokMediumMachine Learning EngineerCompute minimum path sum in a triangle
This problem tests your ability to optimize path calculations in a non-linear data structure using dynamic programming, specifically focusing on space complexity optimization.
Coding & AlgorithmsTechnical ScreenDynamic ProgrammingArraysSpace Optimization - TikTokMediumMachine Learning EngineerCount subarrays summing to target
This problem tests your ability to optimize subarray sum calculations from an O(n^2) approach to O(n) using a hash map for prefix sum tracking.
Coding & AlgorithmsTechnical ScreenArraysHash MapPrefix Sum - TikTokMediumMachine Learning EngineerDetermine frog reachability across stones
This question evaluates dynamic programming, state-space reachability, and constrained transition reasoning, along with skills in hash-based memoization and time/space complexity analysis.
Coding & AlgorithmsOnsite - TikTokMediumMachine Learning EngineerDetermine if a string can be segmented
This question evaluates a candidate's understanding of dynamic programming and string-processing skills, along with algorithmic complexity analysis for segmentation problems.
Coding & AlgorithmsTechnical Screen - TikTokMediumMachine Learning EngineerDifferentiate virtual and pure virtual functions
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Differentiate virtual and pure virtual functions states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen - TikTokMediumMachine Learning EngineerFind and count target-sum subarrays
Find and count target-sum subarrays 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 - TikTokMediumMachine Learning EngineerFind length of longest common subsequence
This problem tests your ability to identify overlapping subproblems and optimal substructure by implementing a dynamic programming solution to find the length of the Longest Common Subsequence (LCS) between two strings.
Coding & AlgorithmsTechnical ScreenDynamic ProgrammingStringsOptimization - TikTokMediumMachine Learning EngineerFind longest substring without repeating characters
This question evaluates proficiency in string processing, duplicate-detection using appropriate data structures, and algorithmic complexity analysis within the Coding & Algorithms domain.
Coding & AlgorithmsOnsite - TikTokMediumMachine Learning EngineerFix a BST with two misplaced keys
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Fix a BST with two misplaced keys states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen - TikTokHardMachine Learning EngineerGenerate all safe queen placements on board
This question evaluates algorithm design for constraint-satisfaction problems, testing skills in search, recursion, backtracking, combinatorics, and state-space pruning.
Coding & AlgorithmsTechnical Screen - TikTokHardMachine Learning EngineerImplement local maxima, bagging, and k-means
This problem tests your ability to implement a sliding window peak detector, a bootstrapping ensemble sampler, and a centroid-based clustering algorithm from scratch.
Coding & AlgorithmsOnline AssessmentAlgorithmsClusteringEnsemble Learning - TubiMediumMachine Learning EngineerImplement K-Means and compare with GMM
This question evaluates understanding and practical implementation of clustering algorithms, specifically K-Means centroid initialization, assignment and update mechanics, convergence criteria and edge-case handling, along with comparative knowledge of Gaussian Mixture Models and the Expectation-Maximization training framework.
Coding & AlgorithmsTechnical Screen - TubiMediumMachine Learning EngineerWeighted Random Sampling by Index
This question tests a candidate's ability to implement weighted random sampling using prefix sums and binary search, evaluating practical algorithm design for probability distributions. It assesses proficiency in translating mathematical probability constraints into efficient data structures, a skill commonly probed in machine learning engineering roles where non-uniform sampling is fundamental to model training and inference pipelines.
Coding & AlgorithmsTechnical Screen - Two SigmaMediumMachine Learning EngineerSolve tree partition and IPO allocation
This question evaluates algorithmic problem-solving skills in tree processing and allocation simulations, specifically assessing understanding of subtree-sum computation for tree partitioning and deterministic round-robin allocation logic for IPO-style share distribution, along with appropriate data structure selection and correctness under edge cases. It is commonly asked in the Coding & Algorithms domain because it measures practical application-level implementation and the ability to analyze time and space complexity rather than purely conceptual proof.
Coding & AlgorithmsOnline Assessment - UberEasyMachine Learning EngineerAnalyze sales with groupby
This question evaluates proficiency in data manipulation and analytics using pandas, specifically the ability to join relational tables and apply groupby aggregations to compute business metrics like total sales, average sales per order, and completion rates.
Coding & AlgorithmsTechnical Screen - UberMediumMachine Learning EngineerChoose K pickup locations minimizing L1 distance
This question evaluates facility-location and spatial optimization skills under the Manhattan (L1) metric, testing algorithm design, combinatorial optimization, and handling geometric data.
Coding & AlgorithmsOnsite - UberMediumMachine Learning EngineerCompute currency conversion via graph search
This question evaluates graph modeling and pathfinding with weighted edges, numerical reasoning about multiplicative rates and floating-point precision, and the ability to analyze algorithmic time and space complexity.
Coding & AlgorithmsTechnical Screen - UberMediumMachine Learning EngineerCompute minimal time to finish dependent tasks
This question evaluates understanding of graph algorithms and scheduling, specifically reasoning about task dependencies, parallel execution, and cycle detection in directed graphs.
Coding & AlgorithmsOnsite - UberMediumMachine Learning EngineerCount connected delivery zones
This question evaluates graph traversal and connected-components detection on grids, measuring competence in grid-based algorithms, neighbor connectivity, and algorithmic analysis of time and space complexity.
Coding & AlgorithmsOnsite - UberHardMachine Learning EngineerFind Robots by Nearest-Blocker Distances
Implement an algorithm to identify all robots in a grid whose four-directional distances to the nearest obstacle or grid boundary match a target query.
Coding & AlgorithmsTechnical Screenmatrixprefix-sumhash-table - UberMediumMachine Learning EngineerFind a Black-Box Convex Function Minimum
This question evaluates proficiency in zero-order optimization and algorithm design, focusing on reasoning about convexity and unimodality when only function evaluations are available.
Coding & AlgorithmsTechnical Screen - UberMediumMachine Learning EngineerFind robots in a grid whose four-direction distances to blockers match a query
Given a grid of robots, blockers and empty cells plus a query of four distances, return every robot whose distances to the nearest blocker or grid edge going up, down, left and right match the query exactly. Tests precise distance definitions, boundary handling and scaling past a per-robot scan.
Coding & AlgorithmsTechnical Screen - UberMediumMachine Learning EngineerImplement a Referral Revenue Tracker
This question evaluates proficiency with data structures and algorithms for hierarchical aggregation and ranking, assessing skills such as maintaining recursive subtree aggregates, handling dynamic inserts, and executing efficient top-k queries; it is in the Coding & Algorithms domain and tests practical application of in-memory data structure design. It is commonly asked to evaluate the ability to design scalable, low-latency in-memory systems that preserve aggregate values across referral trees and support fast query operations while reasoning about time and space complexity trade-offs.
Coding & AlgorithmsOnsite - UiPathMediumMachine Learning EngineerCompute Minimum L-Moves on Infinite Grid
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Compute Minimum L-Moves on Infinite Grid states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen - UiPathMediumMachine Learning EngineerImplement cocktail shaker sort and analyze
This question evaluates a candidate's understanding of sorting algorithms and algorithmic optimization, specifically implementation and enhancement of cocktail shaker sort, plus analysis of time and space complexity, stability, and counts of comparisons and swaps.
Coding & AlgorithmsTechnical Screen - UiPathMediumMachine Learning EngineerProbability a draw-until-threshold score ends at or below a limit
A coding question on probability: a player repeatedly adds a uniformly random number of points until the total reaches a threshold, and you return the probability that the final total is at most a given limit. It tests careful probabilistic reasoning and an efficient computation for inputs up to ten thousand.
Coding & AlgorithmsTechnical Screen - Walmart LabsEasyMachine Learning EngineerFind first non-repeating character
This problem tests your ability to use hash maps or frequency arrays to achieve optimal time complexity when processing character streams or strings.
Coding & AlgorithmsOnsiteStringsHash MapFrequency Array
Tesla
TikTok
Tubi
Two Sigma
Uber
UiPath
Walmart Labs