This year Meta The recruitment pace of AI SDE is generally fast. As long as you pass the OA, the follow-up timeline will basically be "continuous". Based on my actual experience coaching students, the process is broken down in more detail below so that you can clearly see what is being tested at each step and how to prepare.
Meta Official Timeline
- Day 1: Receive OA (CodeSignal)
- Day 3: Submit OA and automatically enter technical screening that night or the next day
- Day 5: Received invitation from Onsite, can make appointment within 3~7 days
- Day 8: Official Onsite Four Wheels
- Day 10-12: Receive final results (AI team feedback is very fast)
The Meta AI team is really anxious to recruit people, and the entire timeline is running very fast.
OA (CodeSignal) real questions + feelings
There are 4 levels in 90 minutes. To be honest, the pace is not easy.
Level 1-2: Warm-up questions
Very conventional, simple string and array operations.
Example:
Group uppercase letters and lowercase letters in a string, keeping the order unchanged.
As long as you can write steadily.
Level 3: Starting to have some flavor
This is the key screening point.
Examples of real questions (condensed version):
Given a grid with dynamic obstacles and maybe one more block every two steps, ask how many paths there are from the upper left to the lower right.
It mainly depends on how clear your DP's thinking is.
Those who write this question smoothly will quickly stand out.
Level 4: Write as much as you like
What I do is a social relationship recommendation, the kind of top-K mutual friends.
AC is not required, just writing the framework is enough.
Onsite (four rounds) - I add real questions and real feelings to each round
Round 1: BQ (dig deep)
This round was actually quite tiring because the interviewer asked very detailed questions.
To give an example of a question at the time:
"Tell me about a time you disagreed with a senior engineer."
Then instead of just letting it go, he asked continuously:
- Why didn't you agree then?
- Do you have data to support this?
- How far did you fight?
- Who gave in in the end?
- If you were to do it again now, would you make the same decision?
Meta's BQ has no useless questions, it really digs "how do you think about problems" to death.
Real feelings:
If your story is made up, you will basically not be able to withstand this kind of questioning; but if it is a true experience, the story will become smoother and smoother.
Round 2: Coding (two questions)
The overall difficulty range is between medium+ and hard-.
Real question 1 (DP + direction restriction):
Given a matrix with cost, walk from the upper left to the lower right, but you can only make at most k turns. Find the minimum cost.
I first verbalized my ideas, starting with how to design the DP state, and then the interviewer asked me to write code.
The core of Meta coding is not AC, but whether you can explain your ideas clearly.
Real question 2 (array segmentation):
Given an array and a target, cut the array into several segments. The sum of each segment is ≤ target. Find the minimum number of segments.
The test points are very straightforward, but there are many boundaries.
My true feelings:
Meta in coding depends very much on your control of boundaries. If you can take the initiative to mention corner case, they will obviously nod.
The third round: system design (AI scenario, not traditional big factory routines)
In this round, I initially thought I would ask about session, cache, and sharding, but it turned out not to be the case at all.
Real questions (real scene version):
Design an AI data processing pipeline, from ingestion → cleaning → feature → model → inference, to connect the whole link.
The interviewer is particularly concerned about three points:
- How do you handle delayed data?
- If features need to be recalculated, how can your pipeline support it?
- How to roll back when the model fails to go online?
This round is only 35 minutes long, so you won’t be able to brag too much, so structured expression skills are key.
Real feelings:
Meta's system design is not like Amazon's routine, but more like "you build a system that can actually be used."
Round 4: AI programming (multi-file debugging, many people overturned)
This is the most unique round of the Meta AI SDE position, and it is also the round for which I have prepared the most.
Give you a bunch of files:
- preprocess.py
- datasets.py
- model.py
- trainer.py
- evaluator.py
- main.py (entry)
you want:
- Understand the code
- Run logic
- Find bugs
- fix bug
- Re-verify
Example of real question bug:
- label encode is inconsistent between training and inference stages (preprocess file)
- The accuracy dimension of evaluator is written inversely
- gradient accumulation reset is in the wrong position (trainer)
Real feelings:
This round depends entirely on whether you have ever written engineering projects, and it cannot be solved by brushing LeetCode.
It’s not that most students can’t write, but they panic because the time is too short and there are too many files.
Prepare recommendations
If you only write questions and don't write projects, the AI programming wheel will be a nightmare.
If you don't organize your BQ carefully, you will drown in the first round.
If you are not familiar with data processing logic, it is easy to get different answers in the third round.
But if you’re a “hands-on, articulate person,” Meta will love it.
Programhelp | The "hidden power" behind your interview
To be honest, it is really too expensive for one person to carry out the VO/OA business of today’s major manufacturers. More and more students come to me and tell me: The questions are not difficult, but the pressure is high, the pace is fast, and the brain freezes when panicked; they have been preparing for a long time, but they are often stuck at the moment when the interviewer asks a question.
This is why so many people later chose to let ProgramHelp Be the “second brain” behind them.
We are not a routine that only relies on AI, but a real-time collaboration team composed of North American active engineers + CS professional background instructors. The format is very restrained but effective, for example:
- Provide real-time voice dialing during VO interviews
- In the OA stage, traceless remote connection (ToDesk) can help you avoid pitfalls and speed up, and maintain the natural operation trajectory.
- When you encounter blind spots while coding, your instructor will discover the nature of the bug faster than you do.
- The behavior is faced with the scene, not memorizing the script, but using the real expression framework of Flax/Google engineers to guide you to the point.
If necessary, anytimecontact ustalk about your timeline and position, and we will give you the most pragmatic plan, which is neither false nor exaggerated, and we will develop a path based on your situation.
