← Back to Directory

Pinterest interview notes, page 10 of 24

Large Enterprises

Most of these Pinterest write-ups come from Machine Learning Engineers (91), then Software Engineers (77) and Data Scientists (51). The most reported rounds are the technical phone screen (168), the system design round (37), the product sense round (14) and the behavioral / leadership round (5).

235 interview notes · updated Sep 2026

Pinterest·Software Engineer·Technical Phone Screen

May 2026
Pinterest security engineer interview, got a single technical question about ransomware containment. Pretty focused, no fluff.
  • How would you prevent ransomware from propagating through a network once it's detected?

“This is the kind of question that sounds straightforward but you can go a dozen different directions.”

View Post

Pinterest·Data Scientist·Technical Phone Screen

May 2026
Pinterest data scientist interview with a pandas-heavy coding problem centered on cleaning and aggregating a transactions dataset. Pretty applied, less algorithmic than I expected.
  • Using pandas, write a lambda function to add a new column that flags transactions where the amount exceeds $40 as high-value purchases.
  • Build a dictionary mapping raw category strings like 'grocery' and 'coffee' to standardized labels, then loop through it to transform the category column in the DataFrame.
  • Aggregate the dataset to get total spend and transaction count per user, and return a clean summary DataFrame.

“Straightforward enough but I second-guessed myself on whether to use apply with a lambda or just a boolean mask.”

View Post

Pinterest·Machine Learning Engineer·Technical Phone Screen

May 2026
Pinterest MLE interview with a classic scheduling/optimization problem. Nothing too surprising but the pruning details matter more than you'd think.
  • Given an array of job durations and k workers, assign every job to exactly one worker so that the maximum total working time across all workers is minimized. Return that minimum possible maximum.

“I went with backtracking first and got it mostly right, but the pruning is where things get tricky.”

View Post

Pinterest·Data Scientist·Technical Phone Screen

May 2026
Pinterest DS interview with a brutal experiment design question built around a botched A/B rollout. The whole thing was one long case study and it went deeper than I expected, covering causal inference, assumption testing, and post-mortem process all in one sitting.
  • An intern accidentally launched an experiment without a control group, so all eligible users got the treatment for 5 days. You have 4 weeks of clean pre-period data. Walk through at least two observational methods you'd use to estimate the treatment effect, and compare them.
  • What assumptions does each method rely on, and how would you design placebo or falsification tests to check them?
  • How do you compute ATT versus ATE in this scenario, and how do you account for seasonality, novelty effects, and calendar confounds when the treatment window is only 5 days?
  • How would you quantify uncertainty in your effect estimates given the observational setup, specifically around weighting or matching approaches?
  • What went wrong with the original experiment setup that allowed this to happen, and what prevention mechanisms would you put in place going forward?

“This took me a while to even orient to.”

View Post

Pinterest·Software Engineer·Technical Phone Screen

May 2026
One-hour phone screen for a Pinterest SWE role. The coding problem was a trip expense settlement question that felt like it assumed you'd seen something similar before, which I hadn't quite.
  • A group of friends go on a trip together. You're given a list of transactions, each with a payer, a total amount, and a list of people the payment covered. Write a function that outputs the minimal set of payments needed to settle all balances between the group.

“My first instinct was to model it as a graph of who owes whom, which got complicated fast.”

View Post

Pinterest·Software Engineer·Hiring Manager Screen

May 2026
Interviewed for a data analyst role at Pinterest. Just one question worth noting, a classic behavioral opener that felt low-stakes but tripped me up more than expected.
  • Tell me something about yourself that isn't on your resume.

“I blanked for a second and rambled about a hobby that had zero relevance to the role.”

View Post

Pinterest·Software Engineer·Technical Phone Screen

May 2026
Pinterest phone screen for a software engineer role. One coding question, pretty focused on sorting and search with some follow-up discussion about edge cases. Nothing too wild but the date comparison piece tripped me up a bit.
  • You're given a list of log entries, each with a date string attached. Sort them by date, then use binary search to find the index of a log entry matching a given target date. How do you compare date strings correctly, and how do you handle duplicates or a date that doesn't exist in the list?

“The sorting part I got fine, but I stumbled on the date comparison piece.”

View Post

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

May 2026
Pinterest ML engineer interview focused entirely on designing a pin search system end to end. It was a dense session covering retrieval, ranking, loss functions, and experimentation, the kind of question where you can go pretty deep on any one piece and still feel like you barely scratched the surface.
  • Design a search engine for Pinterest pins, covering the full ML pipeline from candidate retrieval through ranking.
  • How would you approach candidate generation for pin search, and what retrieval strategies would you consider?
  • Walk me through how you'd design the ranking model, including architecture choices and input features.
  • What loss functions would you use for training the ranking model, and how would you handle negative sampling?
  • Which offline metrics would you use to evaluate the search ranking model before deploying?
  • How would you approach feature engineering for pin search, particularly for image and user behavior signals?
  • How would you set up online evaluation and A/B testing for changes to the search ranking system?

“This was basically the whole interview.”

View Post

Pinterest·Machine Learning Engineer·Technical Phone Screen

May 2026
Pinterest ML engineer round, one algorithmic problem that sounds deceptively simple but has a real O(n) trick buried in it. Left feeling like I probably over-explained the brute force before getting to the good part.
  • Given an array and an odd-sized sliding window, for each window position determine whether the values form a 'bitonic' shape centered on the middle element, meaning strictly decreasing in both directions away from the center. Return the positions where this holds. What is the time complexity of your solution, and can you achieve O(n)?

“Spent way too long on the naive approach, checking each window independently which is obviously O(nk).”

View Post

Pinterest·Data Scientist·Technical Phone Screen

May 2026
Pinterest DS interview with a SQL/Python question centered on policy violation logs. The problem had a performance angle baked in which I didn't fully see coming.
  • Given a table of pin policy violations (with pin_id, violation type, and date), write SQL or Python to return all pin_ids that violated a specific policy type. Then extend your solution so that, given a policy type plus a date range, it retrieves matching pins efficiently using binary search instead of a full scan.

“I wrote the SQL part fine, basic filter on type.”

View Post