Company
Perplexity interview questions
13 practice questions in the style of Perplexity's interviews, covering Coding & Algorithms, System Design, ML System Design, Software Engineering Fundamentals, Machine Learning.
0 easy8 medium5 hard
Perplexity interview questions by the numbers
Last updated
Katkat has 13 Perplexity interview questions. The largest topics are Coding & Algorithms (38%), ML System Design (23%) and Software Engineering Fundamentals (15%). By difficulty: 62% medium and 38% hard. The most common round is Technical Screen (69%). Frequent concepts include Ranking, Scalability, algorithms and Data Engineering.
Topics
- Coding & Algorithms38% · 5
- ML System Design23% · 3
- System Design15% · 2
- Machine Learning8% · 1
Difficulty
- Medium62% · 8
- Hard38% · 5
Interview rounds
- Technical Screen69% · 9
- Onsite23% · 3
- Online Assessment8% · 1
Roles
- Software Engineer85% · 11
- Data Scientist8% · 1
- Machine Learning Engineer8% · 1
Frequent concepts
- Ranking15% · 2
- Scalability15% · 2
- algorithms8% · 1
- Data Engineering8% · 1
- Data Pipelines8% · 1
- data-processing8% · 1
Most mentioned in interview experiences
- 1.Implement Task Dependencies and Failure1 report
- 2.In-Memory File System: Add cd and Relative Path Support1 report
- 3.In-Memory File System: Strict mkdir, touch, ls, rm, rmdir and a Command Runner1 report
Counted from 2 candidate interview experiences on Katkat. How we collect and count
Showing 1–13 of 13 results
This question evaluates a candidate's ability to design and implement data structures and algorithms for managing time-bound resources with non-monotonic (out-of-order) operations, emphasizing correctness and efficiency within the coding & algorithms domain.
PerplexitySoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates skills in large-scale system design including API and third-party integrations, data ingestion and normalization, transactional consistency and idempotency, security and privacy controls, data modeling for multi-currency financial records, and operational concerns like alerts and budgeting.
PerplexitySoftware EngineerSystem DesignTechnical ScreenThis problem evaluates your ability to design a scalable, real-time recommendation system that balances personalization with content discovery in an information-seeking environment.
PerplexitySoftware EngineerML System DesignOnsiteThis question tests the ability to design a high-throughput, real-time pipeline that identifies and ranks trending search queries, requiring trade-offs between freshness, accuracy, and system latency.
PerplexitySoftware EngineerML System DesignOnsiteThis question evaluates competency in diagnosing and mitigating production overloads in Kubernetes-based microservice architectures, emphasizing observability, autoscaling behavior, resource constraints, and incident-response reasoning.
PerplexitySoftware EngineerSystem DesignTechnical ScreenDesign an in-memory task management system that tracks directed dependencies between tasks, prevents cycles, and unblocks dependent tasks upon completion.
PerplexitySoftware EngineerCoding & AlgorithmsTechnical ScreenImplement proportional stratified sampling on an in-memory list of records partitioned by a categorical key, ensuring exact sample size via the largest remainder method and reproducible selection.
PerplexityData ScientistCoding & AlgorithmsTechnical ScreenThis question evaluates understanding of graph-based data structures and algorithms for modeling bidirectional task dependencies, status tracking, and efficient cascading failure propagation in an in-memory task manager.
PerplexitySoftware EngineerCoding & AlgorithmsTechnical ScreenThis English-language summary evaluates a candidate's ability to design a resilient, multi-provider LLM client library encompassing provider management, governance (rate limiting and quotas), resilience mechanisms (health checks, timeouts, circuit breakers), routing (cost- and latency-aware load balancing, retries and fallbacks), observability, security, and concurrency. Commonly asked in the ML System Design domain to assess architectural decision-making and trade-off reasoning for availability, cost, latency, and operational robustness, the question targets practical application and architectural-level thinking rather than purely conceptual or low-level implementation details.
PerplexitySoftware EngineerML System DesignTechnical ScreenThis question evaluates a candidate's ability to design and implement a time-versioned key–value store, assessing knowledge of temporal data structures, versioning semantics, time-travel and range queries, deletion semantics, and rollback/restoration.
PerplexitySoftware EngineerCoding & AlgorithmsOnline AssessmentA multi-part coding exercise that builds an in-memory file system with directories, files and listings over absolute paths, then adds a cd command and relative path support to every operation. It tests tree data structures, path normalization with dot and dot-dot components, consistent error handling and safely refactoring earlier code.
PerplexitySoftware EngineerSoftware Engineering FundamentalsTechnical ScreenA two-part coding exercise to build an in-memory file system: first mkdir, touch and ls with strict path validation and no implicit creation of parent directories, then rm, rmdir and a function that executes command sequences. It tests tree modeling, error handling and working against provided tests.
PerplexitySoftware EngineerSoftware Engineering FundamentalsOnsiteThis problem tests your proficiency in the scikit-learn workflow, specifically focusing on data preprocessing, addressing class imbalance in imbalanced datasets, and selecting appropriate metrics beyond accuracy.
PerplexityMachine Learning EngineerMachine LearningTechnical Screen
Perplexity interview experiences
All 2 →- Phone Screen Rejected After a File System Question Ran Over TimePerplexity · Software Engineer · Technical Screen · Oct 2026Rejected
This was a question already reported on the forum: a file system problem. I got through the first two parts basically on the first try. The interesting thing was that the interviewer kept interrupting me while I was writing, asking what this function does and why I wrote it that way. I said it would be clear once I finished writing. When I was done I walked him through it with an example, and he…
- A 4-Part 'Todo List for AI' Coding RoundPerplexity · Software Engineer · Technical Screen · Apr 2026Rejected
I applied through LinkedIn. The first round was with a recruiter who just asked some basic info, then scheduled a coding round. It had to be done in Python. The coding round question was the "implement todo list for AI" one that's already been posted on the forum. There were 4 parts total. I only got through the first two parts before running out of time. The second part was a pain because every…
More companies
- Meta666
- Amazon653
- Google486
- OpenAI342
- Capital One268
- Microsoft252
- DoorDash241
- Anthropic225
- Uber217
- Apple177
- TikTok176
- Pinterest161
- ByteDance160
- LinkedIn154
- Stripe139
- Snowflake130
- Databricks122
- Airbnb112
- Rippling106
- Oracle104
- Coinbase99
- Netflix97
- NVIDIA95
- Snapchat94
- Citadel90
- Waymo90
- Instacart87
- Roblox84
- Salesforce77
- Optiver76
- Shopify63
- Robinhood60
- Atlassian55
- Hudson River Trading55
- Two Sigma55
- J.P. Morgan53
- PayPal53
- xAI53
- Lyft52
- Tesla52
