← Back to Directory

Reddit interview notes, page 3 of 6

Large Enterprises

Most of these Reddit write-ups come from Machine Learning Engineers (23), then Software Engineers (21) and Data Scientists (5). The most reported rounds are the technical phone screen (29), the system design round (14), the product sense round (5) and the behavioral / leadership round (3).

52 interview notes · updated Jul 2026

Reddit·Software Engineer·Technical Phone Screen

May 2026
Reddit SWE interview that centered on a chat messaging function and quickly turned into a deep dive on caching. Not a lot of breadth but they really pushed on one topic.
  • What would you do if get_chat_messages(id) is being called too frequently and causing performance issues?

“Said cache pretty quickly and felt good about it, but then they kept going.”

View Post

Reddit·Software Engineer·Onsite - System Design / Architecture

May 2026
Reddit system design round focused entirely on a game leaderboard service. Pretty deep dive, covered a lot more ground than I expected for a single question.
  • Design a leaderboard service for a game with tens of millions of players. Walk through the API, storage layer, and how you'd keep core operations fast.
  • How would you design time-windowed leaderboards, like separate daily and weekly rankings that reset on a schedule?
  • How do you handle ties in the leaderboard rankings?
  • Walk me through how you'd support regional leaderboards alongside a global one.
  • How would you implement a 'nearby players' feature that returns players ranked just above and below a given player?
  • How do you handle persistence and recovery for the leaderboard if the in-memory store goes down?

“I jumped straight to Redis sorted sets which felt right, but I spent too long justifying skip lists internally before they nudged me toward tradeoffs with a sharded relational store.”

View Post

Reddit·Software Engineer·Technical Phone Screen

May 2026
Reddit coding screen for a software engineering role. One problem, log processing, seemed deceptively straightforward but had some tricky details around ordering.
  • You're given a long log string where each entry has the format: admin2,add,admin1(executor),timestamp. Write a function that returns a list of admin names sorted by the most recent time they were added.

“The input format took me a second to parse mentally.”

View Post

Reddit·Data Scientist·Technical Phone Screen

May 2026
Reddit data scientist interview with a brutal causal inference question that basically asked you to design a full synthetic control study from scratch, no A/B test allowed. The kind of question where you realize halfway through your answer that you've opened like six cans of worms simultaneously.
  • A high-impact feature can't be A/B tested due to policy or infrastructure constraints, but leadership needs a go/no-go decision. Walk through a complete causal inference analysis plan using synthetic control (or justify a different method). Cover how you'd build the donor pool, choose the pre-intervention window, define primary and guardrail metrics, select predictors and tune weights, run diagnostics and placebo tests, handle sensitivity analyses, analyze heterogeneity, and ultimately map results to a staged launch decision.

“This question is basically nine questions stapled together.”

View Post

Reddit·Machine Learning Engineer·Onsite - System Design / Architecture

May 2026
Reddit ML Engineer system design round focused almost entirely on building a video recommendation system from scratch. The interviewer kept pushing on logging and observability details, which I wasn't expecting to be the main event. Solid experience overall but I left feeling like I underprepared the infrastructure side.
  • Walk me through how you'd architect a video recommendation system covering both the home feed and the 'up next' contextual suggestions.
  • What events would you log for this system, and how do you design the logging schema to support model training later?
  • How do you avoid position bias and other logging pitfalls when collecting training data from the feed?
  • How would you design the feature pipeline, specifically around keeping online and offline features consistent?
  • What labels and objectives would you use to train the ranking model, and how do you balance competing signals like clicks versus watch time?
  • How do you handle latency budget and fallback behavior when the ranking model is slow or unavailable?
  • How would you detect and respond to model or data drift in production?
  • What privacy and data retention considerations would you factor into the logging design?

“I started with the classic two-tower candidate retrieval into a ranker setup, which felt safe.”

View Post

Reddit·Product Manager·Onsite - Product Sense / Strategy

May 2026
Reddit PM interview with a pretty unusual question that threw me off more than I expected. The whole thing was framed around a biology scenario, which I didn't see coming from a tech company.
  • If a vulture's head size doubled, how would that affect its survival and ability to adapt? Walk through your reasoning using root cause analysis.

“I stared at this for a second because, well, vultures.”

View Post

Reddit·Software Engineer·Onsite - System Design / Architecture

May 2026
Reddit system design round for a software engineering role, and they went deep on ML infrastructure. The whole session was basically one giant question about feature stores, which I was not fully prepared for at that level of detail.
  • Design a feature store that supports both offline model training and low-latency online inference. Walk through requirements, ingestion, storage, serving, and everything in between.
  • How would you ensure point-in-time correctness when serving features for offline training?
  • What caching strategy would you use for feature serving, and how would you handle cache eviction?
  • How do you approach reliability and fault tolerance for a feature store, and what SLOs would you define?
  • How would you handle governance, access control, and feature lineage in a feature store used by multiple teams?
  • Walk through how you'd test feature pipelines, including unit, integration, and end-to-end testing plus data validation.

“This was one question but it basically ate the entire session.”

View Post

Reddit·Machine Learning Engineer·Technical Phone Screen

May 2026
Reddit ML engineer screen, one algorithmic question that looked manageable until you actually had to implement it under pressure. The KMP angle is the kind of thing you either know or you don't.
  • Given a string, find the shortest palindrome you can make by prepending characters to the front of it.

“My first instinct was brute force, check every prefix, reverse it, see if the whole thing is a palindrome.”

View Post

Reddit·Product Manager·Onsite - Product Sense / Strategy

May 2026
Reddit PM interview with a product metrics question framed around AirBnB launching in a new market. One question, pretty open-ended, the kind where you can spiral fast if you don't anchor early.
  • AirBnB is expanding into a new region. What metrics would you put on a one-page executive dashboard to measure success?

“The 'one-page' constraint is doing a lot of work here and I almost ignored it.”

View Post

Reddit·Software Engineer·Technical Phone Screen

May 2026
Reddit SWE interview with a moderator privilege tracking problem that gets progressively nastier across three parts. Started manageable, ended with me questioning my life choices around linked list ordering.
  • Design a ModSystem class that initializes from a chronological log of moderation actions (each entry specifying a target user, an action of 'added' or 'removed', the acting user, and a timestamp). Implement a canRemoveMod method that checks whether one moderator has the rank to remove another, and a getModRanking method that returns all current moderators ordered from highest to lowest rank, where rank is determined by how early a user most recently became a moderator.
  • Extend the system to support multiple communities, where each log entry now includes a leading community field. All queries (canRemoveMod and getModRanking) become scoped to a specific community, and a user can hold moderator status independently across different communities.
  • Add a demote operation to the multi-community system. Calling demote on a user should move them exactly one position lower in that community's current moderator ranking. If the user is already last or isn't a moderator, nothing happens. Subsequent calls to getModRanking and canRemoveMod must reflect the updated order.

“The ranking rule is the part that trips you up.”

View Post