Exa AI Technical Screen interview experience
Interview Experience
Interview Format and Outcome The session was a strict 15-minute rapid-fire verbal technical screen. The candidate did not move forward in the hiring process.
Technical Questions 1. **Unit Conv
Full Details
Interview Format and Outcome The session was a strict 15-minute rapid-fire verbal technical screen. The candidate did not move forward in the hiring process.
Technical Questions 1.
Unit Conversion: State the exact number of megabytes contained in one gigabyte. 2.
Probability: Calculate the probability of missing a basket three times in a row, assuming an 80% success rate for making a single shot. * Solution Logic: Calculate the inverse probability (20% chance to miss) and raise it to the power of three ($0.2^3$). 3.
System Design: Design a system to index one million documents, each containing a set of words. * Core Task: Create a mechanism that accepts a single-word query and returns all documents containing that word. * Scaling: Explain how the proposed design handles scaling. * Standard Approach: Implementation of an inverted index.
Process Constraints and Environment *
Time Pressure: The 15-minute limit forced a rushed pace, leaving only approximately five minutes to outline the system design and scaling architecture for the final question. *
Interviewer Interaction: The interviewer maintained a low-energy demeanor and declined to answer clarifying questions. *
Atmosphere: The session lacked conversational elements, functioning strictly as a unidirectional examination.
Topics
About Exa AI Interview Reports
This question was reported by a candidate who interviewed at Exa AI. 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 Exa AI are the higher-signal extractions to take from this report.
For broader preparation context, the Exa AI 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 Exa AI reports consistently are the ones worth investing in; one-off niche problems are not.
During Your Exa AI 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 Exa AI 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.