Software Engineering Fundamentals interview questions

Showing 691–720 of 1208 results

• Design a CRUD API for a document serviceMedium

  Design the create, read, update and delete API for a document service, covering the resource model, endpoints, request shapes and status codes. It tests REST fundamentals plus production concerns such as concurrent edits, idempotent retries, pagination, authorization, deletion semantics and API versioning.

  MintlifyBackend EngineerSoftware Engineering FundamentalsOnsite
• Recreate a Card Interface from a ScreenshotMedium

  Recreate a screenshot-defined card and chip component through extracted design tokens, accessible semantics, responsive layout, and visual comparison.

  MintlifySoftware EngineerSoftware Engineering FundamentalsOnsite
• Should you add an index for a slow query on a large table's unindexed columns?Medium

  A query on a large database table is slow and the columns it filters on have no index: should you add one? It tests reading query plans, weighing selectivity and query frequency against write cost, designing composite or partial indexes, and building an index safely on a busy production table.

  MintlifyBackend EngineerSoftware Engineering FundamentalsOnsite
• Keep GPUs Fed with an Efficient Data-Preparation PipelineMedium

  Diagnose GPU input starvation across storage, CPU preprocessing, batching, transfer, and synchronization, then improve bounded overlap while preserving data correctness.

  Mistral AISoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Set up a Python LLM dev environmentMedium

  This question evaluates practical competencies in Python development environment setup, reproducible dependency management with lockfiles, virtual environment and interpreter management, secrets handling via environment variables, project structuring, and basic API integration.

  Mistral AISoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Debug GPU Resource AllocationMedium

  This problem tests your ability to identify and debug concurrency issues and scheduling logic in a custom GPU resource manager.

  MithrilSoftware EngineerSoftware Engineering FundamentalsOnsite
• Explain and Harden Two Shell CommandsMedium

  Tests deep understanding of Unix shell semantics, process management, file permissions, and standard stream handling by diagnosing subtle failure modes in common shell one-liners and writing robust, production-grade replacements.

  ModalSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Prove an Incremental Shuffle Is UniformMedium

  Tests formal inductive reasoning on randomized algorithms by proving the uniformity of the Fisher-Yates shuffle, and evaluates practical knowledge of common implementation pitfalls like off-by-one bounds and modulo bias.

  ModalSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Sort One Hundred Million DigitsMedium

  Implement counting sort to order 100,000,000 single-digit integers using O(1) auxiliary space, and analyze performance from a hardware and memory-bandwidth perspective.

  ModalSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Build a Race-Free Memory Card Game in ReactMedium

  Work through the state and timing logic for a React memory-card game that remains correct under rapid clicks and restarts. The exercise examines stale closures, input locking, timeout cleanup, stable card identity, accessible interaction, and tests for race-prone transitions.

  MomentFrontend EngineerSoftware Engineering FundamentalsTechnical Screen
• Build an Exactly-Once Crawler and Add Safe ConcurrencyHard

  Build a crawler around a supplied fetch-and-parse API, then add bounded concurrency, atomic discovery, correct completion detection, and explicit failure semantics.

  MongoDBSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Debug a slow concurrent network server under loadMedium

  This question tests your ability to diagnose performance bottlenecks in a multi-threaded network server using I/O multiplexing, focusing on how blocking calls and thread management impact latency.

  MongoDBSoftware EngineerSoftware Engineering FundamentalsOnsite
• Evaluate a Nested Predicate Expression TreeMedium

  Implement an evaluator for a serialized predicate expression tree against JSON documents, testing recursion, AST handling, and field resolution.

  MongoDBSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Explain Modern Python Features and EcosystemMedium

  This question assesses your depth of knowledge regarding modern Python language evolution, the utility of popular libraries, and internal implementation details that impact memory and performance.

  MongoDBSoftware EngineerSoftware Engineering FundamentalsHR Screen
• Implement a Finite Concurrent Web CrawlerHard

  Implement an orchestrator for a finite concurrent web crawler featuring transactional URL state tracking, per-host politeness rate-limiting, classified error handling, and robust termination detection.

  MongoDBSoftware EngineerSoftware Engineering FundamentalsOnsite
• Implement a Lazy Union Iterator Over Two Strictly Sorted IteratorsMedium

  Implement a UnionIterator that lazily merges two strictly sorted iterators of integers or strings into one strictly sorted iterator without duplicates, using constant extra memory. Tests iterator protocol design, one-element lookahead, cross-input deduplication, end-of-stream behavior and edge cases such as empty inputs.

  MongoDBSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Implement a sliding-window rate limiter (n requests per k seconds), then make it per keyMedium

  Coding and design question from a technical screen: implement a rate limiter that admits at most n requests in any k-second sliding window, then make it thread-safe and key-specific. It tests window boundary semantics, amortized complexity, race conditions and locking, per-key state creation and memory bounds.

  MongoDBSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Reason About Recursive Key Search in Nested JSONMedium

  Implement a recursive search function to extract all values associated with a given key from deeply nested JSON documents containing arbitrary combinations of dictionaries and lists.

  MongoDBSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Estimate Greeks and hedging PnLMedium

  This question evaluates understanding of option Greeks (delta, gamma, vega), mental approximation of Gaussian probabilities, and the ability to reason about delta-hedged profit-and-loss under Black-Scholes model misspecification, categorized under Software Engineering Fundamentals for a Data Scientist role.

  Morgan StanleyData ScientistSoftware Engineering FundamentalsTechnical Screen
• Explain forward contracts and optionsEasy

  This question evaluates understanding of financial derivatives—specifically forwards and options—assessing competency in financial instruments, contractual rights and obligations, pricing concepts, and how these concepts inform data-driven modeling for a Data Scientist role.

  Morgan StanleyData ScientistSoftware Engineering FundamentalsTechnical Screen
• Clarify and Design a Streaming Top-K TrackerMedium

  This question tests the ability to design an efficient data structure for maintaining the top-K elements in a high-throughput stream with time-windowing requirements.

  NVIDIASoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Compare Java and Python: Execution, Typing, Concurrency and When to Use EachMedium

  An engineering director asks how Java and Python differ and where each language is stronger or weaker. It tests understanding of execution models, static versus dynamic typing, concurrency and the global interpreter lock, ecosystems, and the judgment to recommend a language for a concrete project.

  NVIDIASoftware EngineerSoftware Engineering FundamentalsOnsite
• Count Distinct Strings With a Hand-Built Hash Table, Then Parallelize It for GPUsMedium

  A coding and concurrency question: count the distinct strings in an array with a hash table built from scratch, then keep the count correct when many threads insert at once. It tests hash table design, locks versus atomic compare-and-swap, and how work division and memory layout affect GPU and CPU performance for a million keys.

  NVIDIASoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Data Pipeline Reliability, Backfills, and Spark OptimizationMedium

  Prepare for a NVIDIA software engineering interview question about data pipeline reliability, backfills, and spark optimization. The prompt highlights practical reasoning, edge cases, trade-offs, and validation criteria without revealing the model answer.

  NVIDIAData EngineerSoftware Engineering FundamentalsTechnical Screen
• Define a Git workflow for CIMedium

  This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Define a Git workflow for CI states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  NVIDIASoftware EngineerSoftware Engineering FundamentalsOnline Assessment
• Demonstrate software engineering fundamentalsMedium

  This interview question evaluates engineering fundamentals, trade-offs, examples, pitfalls, and operational implications in a realistic interview setting. A strong answer for Demonstrate software engineering fundamentals states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  NVIDIASoftware EngineerSoftware Engineering FundamentalsOnsite
• Design a Multi-Producer Multi-Consumer Circular BufferHard

  Design a thread-safe, bounded multi-producer multi-consumer (MPMC) circular buffer supporting blocking operations, timeouts, and graceful shutdown (close-and-drain).

  NVIDIASoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Design a top-build target trackerMedium

  This problem tests object-oriented design and data structure proficiency by requiring the implementation of a tracker that maintains the top-K most frequent entities within a sliding time window of events.

  NVIDIASoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Design an IR for test workflowsMedium

  This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Design an IR for test workflows states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  NVIDIASoftware EngineerSoftware Engineering FundamentalsOnline Assessment
• Explain Amdahl’s law and GPU matmul optimizationMedium

  This question tests the ability to apply Amdahl's Law to real-world hardware acceleration and understand the architectural constraints involved in GPU matrix multiplication.

  NVIDIASoftware EngineerSoftware Engineering FundamentalsTechnical Screen