Recently a mentee participated Meta Platforms SDE Entry-Level Interview. The overall experience can be summed up in one sentence: Coding difficulty is within control, but AI Coding and the design wheel are becoming the links that really widen the gap. AI Coding, in particular, is no longer just about "can you write code?" but examines how candidates can use tools to solve complex problems, verify ideas, and quickly iterate.
The following is a complete review of this interview experience based on the real process, and will provide some more valuable reference directions for students who are preparing for technical positions in large manufacturers.
OA assessment link
OA is conducted on the CodeSignal platform and lasts 90 minutes with a total of 4 levels.
The first two levels are more like a warm-up, mainly focusing on string processing and basic array operations. They are not very difficult and are typical scoring questions. As long as you read the questions carefully and avoid low-level mistakes, you can basically get stable points.
Starting from the third level, the questions become obviously more tricky, such as variations of interval merge, which require stronger boundary processing capabilities and logical disassembly capabilities. Fortunately, each level is equipped with an independent test set, which can be directly run for verification. The debugging cost is not high, and there is no need to spend a lot of time on debugging.
The fourth level is more difficult, but does not require completion. I completed "3 and a half questions" at that time. I didn't have high expectations at first, but I received an email from the recruiter the next day and made an appointment directly for tech screening.
In fact, the core function of this OA is more like filtering out "blind betting players". The recruiter also made it clear: As long as they prepare carefully and perform normally, most candidates can pass, so there is no need to be overly anxious.
The only thing to note is that this link cannot be waived, and no matter how strong the background is, it cannot be skipped.
Onsite Interview Process — Meta Platforms SDE Entry-Level
Behavioral wheel
There are a total of 4 behavioral questions in this round. They all seem to be conventional questions, but they are really very in-depth. The interviewer will not stay on the surface, but will constantly ask for details around your story, from the background to your decision-making, to the results and review. It is normal to basically talk for two or three levels, so you will know if the content is true or false.
High-frequency directions are also relatively typical, such as: have you ever led others, how to advance a project when the deadline is tight, how to deal with disagreements with superiors, how to break down problems when the requirements are vague, etc. The question is not new, but the "thickness" of the answer is particularly important.
What the interviewer wants to see more is your way of thinking - how did you judge priorities at that time? Have you ever realized what you didn't do well enough? Did you come up with a better method later? If you just tell a story about "getting the job done" without reflection, it's easy to appear immature.
If there is no support from real experience, it is basically impossible to withstand continuous questioning, the answers will become more and more empty, and finally the logic will be broken.
Coding wheel
There are two mid-range questions in this round, but they are not pure original questions. Instead, they add a little change to the classic model and test whether the basic skills are solid.
The first question is a bit like a variant of LeetCode 46 or 113, requiring pruning during the search process. As long as the recursive structure is designed cleanly and the boundaries are clear, it is actually not difficult to write. It is a question type that "sees whether the idea is clear".
The second question is more about data structures, such as trie + prefix matching, extending functions on existing classes; it may also test the basic understanding of suffix array. The overall feeling is not to get stuck on the algorithm, but to see if you really understand why these structures are suitable for this scenario.
System Design Wheel
For Entry-level, this round is actually quite friendly and the scope will not be particularly large. A common question type is "Design a system for Instagram", such as lightweight recommendations, auction services, etc.
Note that this is not for you to talk about a super complex distributed architecture, but to focus more on MVP thinking - build the minimum runnable version first, and then consider expansion.
I split the system into three layers:
- API entrance + current limit, first ensure that the system can handle requests
- Data flow processing layer, responsible for core logic
- Caching + basic sorting strategy to improve performance
Don’t go for fancy, but be clear.
To be honest, the 35 minutes of thinking time is very tight, and there is no time to expand on many points that I originally wanted to discuss in depth. However, the interviewer will usually help you control the scope and not let the discussion diverge indefinitely. The focus is still on your ability to break down the problem.
Note that Meta is extremely sensitive to high concurrency. Once you mention the increase in user scale, the interviewer is likely to immediately ask:
- How to limit the flow?
- How to avoid hot spots?
- How to ensure cache consistency?
So, when preparing, it is recommended to give priority to strengthening the basic knowledge of high concurrency instead of crazily memorizing architectural terms.
AI Coding Wheel
This round is the key to really opening up the gap. It is not supported in all languages, I chose Python to do it.
The entire assessment is divided into two steps:
The first step is to fix the bug. The interviewer directly gave me a feed ranking tool library of five or six files, and as soon as I started, there were test cases that failed. I originally wanted AI to sort out the entire code structure for me first, but the interviewer directly requested that I must first locate the problem based on the failed use case. I sorted it out by myself for a long time. After finding the bug, I asked AI to help confirm the code logic, and finally fixed the bug.
The second step is to write the solver. I first talked about the brute force solution, and took the initiative to say that this method would time out, and then brainstormed with the AI, and finally decided to use backtracking with pruning.
Tip: The AI effect used in this round is not as good as ChatGPT-3, but as long as the prompt is specific, it is still very useful.
Experience of landing Meta
This classmate made an appointment with programhelp two weeks before the interview. Interview assistance , and finally got the offer successfully. If you are applying for a major company, or have already received an interview but are not sure whether you can perform stably, it is recommended that you make targeted preparations as early as possible. To some extent, the interview is also a competition with poor information - if you prepare in the right way, the probability of getting an offer will often be significantly magnified.
