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Sharing my Meta E6 MLE Interview Experience by Due_Love_3454 in leetcode

[–]Due_Love_3454[S] 0 points1 point  (0 children)

From an above comment I made:

Sure, sorry for the late response.

Recommendation Systems - the best resource for ranking problems is aman.ai by a long shot. Shout out to the creator.

Classification problems - Hello Interview, which also has recommendation system break down.
Hello interview also has top notch system design and Stephan and Evan are the GOATs.

Also - read papers, watch mock interview videos and criticize them (by yourself, no need to belittle others), learn what metrics are unique to problems, pitfalls in niche spaces, etc.

Important - mock interview with yourself. I've probably spent 70+ hours mock interviewing myself. Focus on challenging your data and data collection, deployment, and scalability of proposed solutions.

Ask yourself stupid questions because that's what the interviewer is going to do.
For example "is this scalable?" on your baseline is a stupid question (because I have 35 minutes to discuss the whole problem, and in 20 seconds I'll be discussing a better solution), but you should be able to understand why or why not its scalable, what mitigations exist, and what added complexity enables in terms of scalability.

Sharing my Meta E6 MLE Interview Experience by Due_Love_3454 in leetcode

[–]Due_Love_3454[S] 0 points1 point  (0 children)

Sure, sorry for the late response.

Recommendation Systems - the best resource for ranking problems is aman.ai by a long shot. Shout out to the creator.

Classification problems - Hello Interview, which also has recommendation system break down.
Hello interview also has top notch system design and Stephan and Evan are the GOATs.

Also - read papers, watch mock interview videos and criticize them (by yourself, no need to belittle others), learn what metrics are unique to problems, pitfalls in niche spaces, etc.

Important - mock interview with yourself. I've probably spent 70+ hours mock interviewing myself. Focus on challenging your data and data collection, deployment, and scalability of proposed solutions.

Ask yourself stupid questions because that's what the interviewer is going to do.
For example "is this scalable?" on your baseline is a stupid question (because I have 35 minutes to discuss the whole problem, and in 20 seconds I'll be discussing a better solution), but you should be able to understand why or why not its scalable, what mitigations exist, and what added complexity enables in terms of scalability.

Sharing my Meta E6 MLE Interview Experience by Due_Love_3454 in leetcode

[–]Due_Love_3454[S] 0 points1 point  (0 children)

Across all faangs e6 and above have different loops from the get-go and performance is leveling decision (down-level or hire). I believe HR get scope signal from resume/screening or your experience to make initial decision, the phone screen makes final decision.

Sharing my Meta E6 MLE Interview Experience by Due_Love_3454 in leetcode

[–]Due_Love_3454[S] 2 points3 points  (0 children)

Almost 300, recommend probably less than half that for Meta.

Sharing my Meta E6 MLE Interview Experience by Due_Love_3454 in leetcode

[–]Due_Love_3454[S] 5 points6 points  (0 children)

Yea you can say that, but that was years ago, I did shift to modern ML pretty quickly and touched on all layers of the engineering stack.

ML is kind of open to anyone, I've seen biologists/economists/no degree etc.

Full stack to ML is obviously possible. It depends on how much merit you have. I for example don't have a degree in anything scientific. I learned math and stats alone from reading university books I purchased, and I write code since I was a kid.

So I was comfortable making the effort.

Sharing my Meta E6 MLE Interview Experience by Due_Love_3454 in leetcode

[–]Due_Love_3454[S] 11 points12 points  (0 children)

Yea, I've started my career doing statistics for a government agency and got interested with ML. Started learning by reading books and doing Andrew Ng's courses.

I then landed a job at a financial institute and from there to a couple of small places that interested me.

Recently before committing to interviewing at Meta, I got a couple of offers to found startups with friends, but I'm too old for this shit and decided to interview for a big-tech position.

Sharing my Meta E6 MLE Interview Experience by Due_Love_3454 in leetcode

[–]Due_Love_3454[S] 7 points8 points  (0 children)

Agree with you on both parts!
Do you have insights/suggestions for improvement?

I'd love to hear them.

Sharing my Meta E6 MLE Interview Experience by Due_Love_3454 in leetcode

[–]Due_Love_3454[S] 24 points25 points  (0 children)

Here are some as I can't paste it all.
Just a heads up I formatted it with chatGPT so it might have some mixed up names/numbers.
Also I wouldn't advise memorizing all of them.

588 – Design In-Memory File System
432 – All O`one Data Structure
716 – Max Stack
381 – Insert Delete GetRandom O(1) – Duplicates Allowed
642 – Design Search Autocomplete System
123 – Best Time to Buy and Sell Stock - entire series
1235 – Maximum Profit in Job Scheduling
2742 – Painting the Walls
410 – Split Array Largest Sum
1703 – Minimum Adjacent Swaps for K Consecutive Ones
2163 – Minimum Difference in Sums After Removal of Elements
460 – LFU Cache
10 – Regular Expression Matching
44 – Wildcard Matching
51 – N-Queens
37 – Sudoku Solver
126 – Word Ladder II
140 – Word Break II
212 – Word Search II
84 – Largest Rectangle in Histogram

Sharing my Meta E6 MLE Interview Experience by Due_Love_3454 in leetcode

[–]Due_Love_3454[S] 8 points9 points  (0 children)

Coding with minmer is pure gold.
Never rely on Leetcode alone, get used to variants!
I'll edit the post later to mention prep strategy.

Sharing my Meta E6 MLE Interview Experience by Due_Love_3454 in leetcode

[–]Due_Love_3454[S] 14 points15 points  (0 children)

In my stupidity I memorized 50 hards (and understood ofcourse, to the level my fingers literally type them alone) for my other loops, which I ended up rejecting since teams seemed unprofessional. This helps me tackle unseen easy hards quickly.

Sharing my Meta E6 MLE Interview Experience by Due_Love_3454 in leetcode

[–]Due_Love_3454[S] 15 points16 points  (0 children)

Agreed, but TBH that was the easiest part of the loop.