I just helped a student recently. Airbnb I had a SDE new grad interview at Airbnb, and the whole process was very smooth, and finally I got the onsite. I feel that the overall pace of Airbnb's interviews is almost the same as that of Google and Meta, but it has its own characteristics: the questions are not strange, but the investigation points are very comprehensive, and coding + system design + behavioral should all pass the test. I would like to take this opportunity to organize a complete interview experience, and hope that it will be helpful to students who are preparing for Airbnb or similar big factories.
Background of trainees
This student has a master's degree in CS from a top 50 company in the U.S. He had done a 3-month internship in a medium-sized Internet company, and had brushed up on LeetCode, but he basically hadn't practiced system design, and he was quite rusty in behavioral part at first. Since his goal is to work for a top-tier company like Airbnb, he approached us before the interview, hoping that he could be more skillful in coding, system design, and behavioral storytelling.
AirbnbInterviews Real live restoration
Round 1: Coding
At the beginning of the interview, the Airbnb guy threw out a variant of the weighted graph shortest path question. The question is not a common original question, and you need to modify Dijkstra yourself.
The trainee actually understood the idea at the time, but when writing the code, he suddenly got stuck on the boundary case. The interviewer was staring at his screen, his palms were sweating, and he kept debugging.
At this time, we reminded in the headset: "Don't panic, take a small example first, run the path step by step." The trainee did as he was told, and immediately found that the problem was in the initialization, and the code passed all the tests after he patched it up. the interviewer watched him calmly find out the bugs, and nodded his head and said, "Good catch."
Round 2: Coding (Array + Hashmap)
In the second round, the question was to find a pair in an array, requiring O(n). The trainee's first reaction was to write a brute force, resulting in the interviewer immediately asking, "Can you optimize that?"
The trainee was a bit flustered and paused for almost ten seconds, which made the atmosphere a bit awkward. We immediately prompted him to "think about map index", and he started to write a hashmap solution, which finally reduced the time complexity to O(n).
The interviewer also asked, "What if the input is stream?" The participant didn't respond at first. The trainee didn't respond at first, so we hurriedly hinted in the headset: "online processing, consider sliding window", so he answered smoothly, and the scene was immediately stabilized.
Round 3: System Design (URL Shortener)
This round is actually the one that trainees fear the most, after all, new grad doesn't have much experience with system design. The questions are classic URL shortener.
At first, he started with "write a function to make a long URL short", completely ignoring storage and scalability. The interviewer immediately followed up with, "What if you have hundreds of millions of users?"
At this point, we reminded him, "Start with the database schema, hash conflict, and scalability. He immediately talked in the direction of "distributed storage + key-value database + collision solution". The interviewer nodded a few times and asked "How do you think it will scale to global users? This last round was the highlight of the interview, which was totally unexpected.
Round 4: Behavioral (Airbnb is big on cultural fit)
This round had the most relaxed atmosphere, but it was also the easiest to flip. The interviewer asked a killer question:
"Tell me about a time you disagreed with your manager."
The trainee originally prepared an example of a disagreement with an internship supervisor over feature priority, but spoke in too general terms. The interviewer followed up with, "What was the specific communication? What was the outcome?"
The trainee was visibly stuck and his voice was getting lower and lower. We immediately reminded him to follow the STAR frame filler details:
- Situation: The project deadline is very tight, and the mentor asks for additional features.
- Task: he feels it will affect the core deliverable.
- ACTION: He wrote the benchmark, showed the data to his mentor, and suggested alternatives.
- Result: The final program was adopted and the project was delivered on time.
He went down the line, logical and clear, and finally added "It taught me how to use data to persuade rather than emotions", the interviewer smiled with satisfaction.
final result
Less than a week after the interview, HR called and gave me a direct offer. Airbnb Software Development Engineer New Grad offer .
The trainee was especially happy, saying that he had been worried that he would fail in coding because of nervousness, but he didn't expect system design and behavioral to get high scores instead. The most important thing is that there is someone to remind you when you are stuck, so that you won't panic and crash completely.
The secret to getting full marks even in the field
This case is actually particularly illustrative:
Many students Brush a lot of questions, but when it comes to the interview will be easy to nervous, jam; real interview test is not only solve the problem, but also on-the-spot thinking, expression and stability; sometimes just a reminder, can be from the "to hang" into the "stable".
Programhelp offers this kind of no-trace remote voice assistance service:
Coding question ideas stuck, timely point of view of the key direction;
System design Don't know how to expand on that, help you run through the framework;
Behavioral answers are too general, reminding you of the STAR framework to fill in the details;
The whole process is seamless and completely unnoticeable to the interviewer.
If you are also preparing for Airbnb, Google, Meta, such a high bar interview, do not want to fight alone, you can consider letting us do your invisible backup. a lot of students is to rely on this last link, from the "nearly hung up" reversal into the take down of the big factory offer.
