How Reddit Interviews in 2026: Process, Questions & What They Score

• Compute the edit distance between two strings.Tests dynamic programming over two sequences with an O(mn) table and reconstruction of the edit operations.
• Print all combinations of numbers from 1 to n that sum to n.Tests backtracking with pruning and avoiding duplicate combinations while enumerating integer partitions.
• Implement an LRU cache with O(1) get and put operations.Tests pairing a hash map with a doubly linked list so lookups, inserts and evictions all stay O(1).
• Given a set of comment threads, flatten them into the order the UI would render them.Tests depth-first traversal of a forest with a stable child ordering, done iteratively when depth is large.
• Merge k sorted streams of post IDs by timestamp.Tests a k-way merge with a min-heap keyed on timestamp and handling of streams that end at different times.
• From an event log, find the top k most active users in the last hour.Tests hash-map counting inside a sliding time window followed by a heap or partial sort for the top k.
• Given a list of posts with timestamps and upvote counts, find the top K posts within a sliding time window.Tests maintaining a window over timestamps together with a heap or ordered structure ranked by upvotes.
• Given a nested comment structure as a flat list with parent IDs, reconstruct the comment tree and return a depth-first traversal.Tests building a parent-to-children map from parent IDs and emitting a depth-first traversal without recursion limits.
• Find all groups of posts that share at least one common tag (a connected components variant).Tests union-find or BFS over an implicit graph where posts are connected through shared tags.
• Given a stream of user actions, detect users who have performed a specific sequence of actions within a time limit.Tests per-user state machines over a timestamped stream with expiry of stale partial matches.
• Design a hit counter.Tests a time-bucketed circular buffer or deque so recording hits and counting the last window stay amortized O(1).
• Group a list of strings by a specified criterion.Tests choosing a canonical key per string and bucketing with a hash map; the source names only the pattern, not the criterion.
• Word Ladder: find the shortest transformation sequence between two words, changing one letter at a time.Tests BFS shortest path over an implicit word graph with neighbour generation by single-letter substitution.
• Build a tennis game with scoring and state tracking as an object-oriented modelling problem.Tests class design and encapsulated state transitions; a 2024 Blind post and techscreen also report an OOP and API-design emphasis.
• Design and implement a small comment-tree data structure that supports a specified set of operations.Tests low-level design: API ergonomics, testable code and room for the next requirement in an in-memory tree.
• Design an API rate limiter with configurable behaviours.Tests token bucket versus sliding window algorithms and per-key configuration at the low-level design layer.

Reported problems, listed so you know what to expect. Practice them in your own editor or on the platform you prefer; SupaCV's practice mode coaches how you talk through them.

• Design Reddit's home feed: how would you generate and rank a personalized feed for a user subscribed to 500 communities?Tests fan-out on write versus read, ranking pipeline stages, per-user caching and hot community handling.
• Design a real-time notification system for roughly 100 million daily active users, for example delivering comment reply alerts within one second.Tests fan-out, push versus pull delivery, queueing, deduplication and latency targets at high DAU.
• Design a distributed task scheduler.Tests job persistence, leader election, retries, idempotency and at-least-once versus exactly-once execution.
• Design a content distribution system for Reddit's image and video assets.Tests edge caching, origin and transcoding pipelines and cache invalidation for media at scale.
• Design a real-time recommendation engine for the home feed.Tests candidate generation, feature stores, online versus offline ranking and freshness constraints.
• Design a vote counting system that handles about 10,000 votes per second, including anti-abuse handling.Tests write batching, sharded counters, eventual consistency and abuse detection signals.
• Design the comment section for a Reddit post: how do you store, load and update a deeply nested comment tree at scale?Tests tree storage models such as adjacency or materialized path, subtree pagination and update propagation.
• Design comment ranking for a single post with hundreds of thousands of replies.Tests scoring functions, partial loading, caching of ranked subtrees and consistency as new votes arrive.
• Design the hot ranking for a subreddit's front page.Tests time-decayed scoring, periodic recomputation and caching of ranked lists per community.
• Design the content moderation backend: a pipeline processing about 1 million posts per hour with sub-minute time-to-moderation for high-confidence violations.Tests queueing, tiered classifiers, prioritisation by confidence and human review workflows.
• Design the Reddit Answers retrieval-augmented generation pipeline.Tests retrieval indexing, embedding search, prompt assembly and latency and cost trade-offs.
• Design an autocomplete system.Tests trie or prefix index design, top-k ranking per prefix and update freshness.
• Design Slack.Tests real-time messaging, WebSocket fan-out, channel data modelling and message ordering.
• Design TikTok.Tests video upload pipeline, feed ranking and CDN delivery at consumer scale; filed under both PM and SWE on Exponent.

Reported problems, listed so you know what to expect. Practice them in your own editor or on the platform you prefer; SupaCV's practice mode coaches how you talk through them.

• Tell me about yourself.
• Tell me about a time you made a mistake.
• Tell me about a failure and the explicit lessons you took from it.
• Tell me about your most impactful project.
• Tell me about a project you are proud of and owned end to end.
• Tell me about the projects on your resume and how they fit what this team needs.
• Tell me about something you shipped that broke in production. Walk me through the first ten minutes.
• How would you handle an engineer on your team who repeatedly causes production issues or breaks the build?
• How do you balance paying down technical debt against shipping new features?
• Tell me about a time you had to balance shipping quickly with maintaining quality. How did you make that trade-off?
• Tell me about a time you disagreed with a manager, a peer or the technical direction your team was taking, and how you raised and resolved it.
• Tell me about a time you had to make a technical decision with incomplete information. How did you decide, and how did you communicate the trade-offs to stakeholders?
• Describe a project where you had to collaborate across multiple teams. What was the biggest communication challenge and how did you address it?
• Describe a project where the requirements changed significantly mid-execution. How did you adapt?
• How do you personally use Reddit, which subreddit do you actually use and why, and what would you change or improve about the product?

• You are on the Reddit video team. How would you work with the Feeds team to rank videos higher?
• Help Reddit expand into Japan.
• Imagine Airbnb is launching in a new region. Define the success metrics for a one-page dashboard for executives.
• Should Reddit pay admins? Why?
• Define the success metrics for a launch, design the A/B test, and do the root cause analysis when a metric moves.
• Take-home: write a PRD for a new Reddit product, later reviewed in an executive interview.

• What is overfitting or underfitting? Which models are most likely to experience this, and why?Tests bias-variance understanding and which high-capacity model families overfit; filed under both DS and MLE on Exponent.
• Explain the differences between L1 and L2 regression.Tests Lasso versus Ridge penalties, sparsity and coefficient shrinkage; wording as submitted to Exponent under MLE.
• What do you do when you have missing data, different feature scales, or a model that is overfitting or underfitting?Tests imputation, feature scaling and regularization choices in a practical ML workflow.
• Design a product recommendation system.Tests candidate retrieval, ranking models, cold start and offline versus online evaluation; filed under MLE on Exponent.

Reported problems, listed so you know what to expect. Practice them in your own editor or on the platform you prefer; SupaCV's practice mode coaches how you talk through them.

Reddit's process has 7 stages, in order: Application or recruiter outreach, Recruiter screen, Technical phone screen, Virtual onsite loop, Behavioral, values and hiring manager conversation, Team match, debrief and offer, Track variation: product management loop.

Reddit evaluates candidates against Reddit values (careers page): Reddit's mission first, Make something people love, Evolve, Add value, Default open.

Reddit's question bank spans 5 categories: Coding and algorithms; System design; Behavioral and values; Product sense and analytics (PM track); Machine learning and data science.

This playbook is medium confidence, compiled from 26 public sources, and last verified September 5, 2026. It describes one well-documented shape of Reddit's interviews, not a guarantee of what any individual loop will look like.