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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 4321–4350 of 4616 results
- UberMediumSoftware EngineerSolve Prime Jumps and Pipeline Scaling
This question evaluates algorithmic problem-solving skills in constrained path optimization and resource-allocation throughput maximization, including concepts such as graph modelling with prime-step constraints, dynamic programming, number-theoretic reasoning, and combinatorial optimization.
Coding & AlgorithmsTechnical Screen - UberHardSoftware EngineerSolve Wonderful Strings and Grid Queries
This problem tests your ability to optimize string transformations using bitmask dynamic programming and to perform efficient range-based queries on a grid using a 2D data structure or sweep-line approach.
Coding & AlgorithmsTechnical ScreenBitmaskDynamic ProgrammingOffline Queries - UberMediumSoftware EngineerSolve two interview coding problems
These two problems evaluate algorithmic problem-solving skills: the first focuses on spatial reasoning and grid-based distance computation relative to obstacles, while the second targets tree traversal and character-frequency reasoning for ancestor-path palindrome checks.
Coding & AlgorithmsTechnical Screen - UberHardSoftware EngineerSort a Matrix into Snake Order Using Adjacent Swaps
Construct any legal adjacent-swap sequence that sorts a numbered matrix into snake order, prove correctness, validate the output, and discuss reducing swap counts.
Coding & AlgorithmsTechnical Screen - UberEasySoftware EngineerSort a String of Clothing Sizes
This problem tests the ability to perform a custom sort on a constrained set of characters using an O(n) counting approach rather than a standard comparison-based O(n log n) sort.
Coding & AlgorithmsTechnical ScreenSortingCounting SortString Manipulation - UberMediumSoftware EngineerSort by squares and find k-th smallest
This question evaluates array manipulation, ordering by derived keys (squares/absolute values), order-statistics reasoning, and algorithmic complexity analysis within the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen - UberMediumSoftware EngineerTrack Customer Referral Revenue
This problem tests your ability to model a tree structure and maintain aggregated values across subtrees using recursion or iterative tree traversal.
Coding & AlgorithmsTechnical ScreenTreesRecursionDFS - UberMediumMachine Learning EngineerWhere to apply ML in a task flow from customer request to driver-uploaded evidence
An ML system design discussion about a task platform: walk the end-to-end flow from a customer submitting a task to a driver completing it and uploading evidence, and identify where machine learning and LLMs add value. Tests prioritization, model framing, labels, evaluation and risk handling.
ML System DesignTechnical Screen - UberMediumData ScientistWrite SQL and Pandas for Uber Trips
This question evaluates SQL and Pandas data manipulation competencies, including joins, time-based filtering, handling NULLs, aggregations, rate and ratio calculations, and windowed comparisons over grouped city-day data.
Data Manipulation (SQL/Python)Technical Screen - UberMediumData ScientistWrite SQL/Python for CTR analytics
This question evaluates proficiency in data manipulation and analytics, covering SQL windowing and deduplication for time‑windowed cohort metrics (48‑hour unique CTR) as well as practical Python model evaluation tasks such as precision‑recall plotting, weighted F1 threshold selection, and precision@top‑k.
Data Manipulation (SQL/Python)Technical Screen - 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 - UiPathMediumSoftware EngineerCompute longest distinct substring, case-insensitive
This question evaluates competency in string processing, character normalization for case-insensitivity, algorithmic complexity analysis, and handling large-scale or streaming inputs.
Coding & AlgorithmsTechnical Screen - UiPathMediumSoftware EngineerDescribe project scope and ownership
This question evaluates ownership and technical leadership, including end-to-end project execution, architectural and product decision-making, trade-off analysis, and the ability to quantify impact under constraints.
Behavioral & LeadershipTechnical Screen - UiPathEasyMachine Learning EngineerExplain Core ML Fundamentals
This question tests your conceptual understanding of how fundamental components of neural networks and predictive models affect optimization, generalization, and performance.
Machine LearningTechnical ScreenGradient DescentRegularizationActivation Functions - UiPathMediumMachine Learning EngineerExplain Transformer Layers and FFN Rationale
This interview question evaluates core ML concepts, assumptions, math intuition, training/evaluation trade-offs, and practical failure modes in a realistic interview setting. A strong answer for Explain Transformer Layers and FFN Rationale states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Machine LearningTechnical Screen - UiPathHardSoftware EngineerExplain database design and consistency
This question evaluates proficiency in database design and consistency concepts, covering competencies such as data modeling, datastore selection, partitioning and indexing strategies, consistency semantics, operational trade-offs, validation and testing, and privacy/compliance considerations.
System DesignTechnical 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 EngineerLLM fundamentals: Transformer internals, beam search decoding, and LoRA fine-tuning
An LLM fundamentals question that asks you to explain Transformer internals such as scaled self-attention, multi-head attention, positional information and causal masking. It also covers how beam search decoding compares with greedy decoding and sampling, and how LoRA reduces the cost of fine-tuning.
Machine LearningTechnical 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 - UiPathMediumMachine Learning EngineerReliable LLM tool calling: format control, failure recovery, and runaway loops
An LLM agent question on tool calling: how a model invokes tools, how to keep tool calls in a valid format, how to make tool use stable and fix wrong calls, and how to handle tool-call loops that run too long. It tests practical reliability engineering for production agents.
Machine LearningTechnical Screen - UiPathMediumMachine Learning EngineerWalk through resume and handle ambiguity
This question evaluates a candidate's ability to communicate technical career history, quantify project impact, and demonstrate leadership and ambiguity-handling skills relevant to a Machine Learning Engineer role.
Behavioral & LeadershipTechnical Screen - UpstartMediumData ScientistAnalyze HT vs HH stopping-time probabilities
This question evaluates understanding of discrete probability, stopping-time analysis, pattern occurrence in Bernoulli sequences, derivation of PMFs and expectations, and the ability to generalize results to biased coins.
Statistics & MathTechnical Screen - UpstartMediumData ScientistCalculate Average Event Value by User ID
This question evaluates a candidate's skill in group-wise aggregation and data transformation on JSON-like event streams, specifically computing per-user average metrics and producing ranked results.
Data Manipulation (SQL/Python)Technical Screen - UpstartEasyData ScientistCalculate Particle Survival Probability After Time t
This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Calculate Particle Survival Probability After Time t states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Statistics & MathTechnical Screen - UpstartMediumData ScientistCalculate User Revenue and Session Duration in Python
This question evaluates proficiency in data manipulation and time-series event processing in Python, focusing on per-user revenue aggregation and sessionization to compute average session duration.
Data Manipulation (SQL/Python)Technical Screen - UpstartMediumSoftware EngineerCompute buffet revenue with capacity and waiting
This question evaluates event-driven simulation and state-management skills, including handling customer lifecycle, capacity constraints, FIFO queuing behavior, and revenue aggregation.
Coding & AlgorithmsTechnical Screen - UpstartEasyData ScientistCorrect length-biased sampling from family-size survey
This question evaluates understanding of length-biased sampling and inference under sampling bias, specifically how sampling by individuals (children) differs from sampling by households when estimating family-size probabilities.
Statistics & MathTechnical Screen - UpstartMediumSoftware EngineerDecode an anagram sentence using vocabulary constraints
This question evaluates string manipulation, anagram detection, and constrained dictionary mapping skills, testing attention to character-level constraints and correct disambiguation among similar vocabulary entries.
Coding & AlgorithmsTechnical Screen - UpstartMediumData ScientistDesign Push-Notification System for Airport Surge Pricing
Design Push-Notification System for Airport Surge Pricing evaluates core ML concepts, assumptions, math intuition, training/evaluation trade-offs, and practical failure modes in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Machine LearningTechnical Screen - UpstartHardData ScientistDesign a Real-Time Personalized Ad Selection System
This interview question evaluates core ML concepts, assumptions, math intuition, training/evaluation trade-offs, and practical failure modes in a realistic interview setting. A strong answer for Design a Real-Time Personalized Ad Selection System states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Machine LearningTechnical Screen
Uber
UiPath
Upstart