Ramp 2025 Online Coding Assessment for Applied AI Engineer Position
Question Details
This post was last edited by Anonymous on 2025-09-29 10:38. I applied for an Applied AI Engineer position at the end of September and immediately received an online assessment (OA) invitation. It was
Full Details
This post was last edited by Anonymous on 2025-09-29 10:38. I applied for an Applied AI Engineer position at the end of September and immediately received an online assessment (OA) invitation. It was a 3-day, CodeSignal platform, 45 minutes with only one question. Although I
passed smoothly in about 25 minutes, I received a rejection email on QQ before even finishing the OA. Here's my attempt to improve my luck: Given a string of timestamped requests, write a rate limiter. The limiter should decide whether to accept or reject requests based on the number of requests from the same IP address within a time window.
Input: timestamps (request timestamps sorted by time), ipAddresses (source IP for each request), limit (maximum number of requests that can be accepted from the same IP within a time window), timeWindow (time window length)
Output: An array where position i is 1 if the i-th request is accepted, and 0 if
rejected.
Example: timestamps = [1600040547954, 1600040547957, 1600040547958] ipAddresses = ["127.105.232.211", "127.105.232.211", "127.105.232.211"] limit = 1, timeWindow = 3 Output = [1, 0, 1] Since the input is already sorted by time, a sliding window + hashmap can be used. To record the legitimate request time queue for each IP address, the question isn't particularly tricky, but it's a free OA (Official Assessment). Good luck to everyone!
About This Question
This is a reported interview question from a ramp interview for a swe role during the oa round reported in 2025.
It covers the following topics: Array, Hash Table, Strings, Sliding Window, Queue, Sliding Window, Rate Limiter, Hash Table, Queue, Arrays .
Difficulty rating: Hard
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About Ramp Interview Reports
This question was reported by a candidate who interviewed at Ramp. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.
Use this question as one calibration data point, not a memorization target. Companies typically rotate their question pools every 2-4 months; the exact wording of a 2024 question may differ from what you encounter today. The underlying pattern, difficulty level, and follow-up depth at Ramp are the higher-signal extractions to take from this report.
For broader preparation context, the Ramp interview process typically includes a recruiter screen, one or two technical phone screens, and a 4-5 round on-site loop covering coding, system design (at L4+ levels), and behavioral. Reports tagged on LeakCode show the round-by-round distribution and typical difficulty calibration. To browse questions filtered by round type and seniority, use the company hub linked above.
How To Practice This Type of Question
Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.
Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in Ramp reports consistently are the ones worth investing in; one-off niche problems are not.
During Your Ramp Round
Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.
The single most predictive failure mode in Ramp reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.