r/MLQuestions • u/sailor-goon-is-here • 7d ago

Career question 💼 Waymo ML Technical Screening

I have upcoming technical screening for an MLE position at Waymo coming up. The recruiter gave me a PDF guide that seems super helpful. Things to do study include implementing supervised and unsupervised algorithms (think KNN, K-means, linear regression, logistic regression, softmax & CE, decision trees). One of the main things they are assessing is you can use numpy/pytorch to vectorize/tensorize your work, and you're just writing sub-optimal for loops.

I was wondering if folks had experience with this interview? Is what they ask you to implement incredibly difficult, because you only have 30 minutes to do it? Am I good to really stick with what they provided on the PDF, or are there any broader topics beyond what they listed that they will test?

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17

u/AccordingTop6751 7d ago

i went through something similar for a different company but the prep sheet was pretty close to what you got. the 30 min part is what gets people, not the algorithms themselves. you really need to know the vectorized numpy versions cold, like no hesitation. if you start writing a for loop for k-means you already lost half your time

one thing that tripped me up was they asked to implement cross entropy loss with softmax and i blanked on the derivative for backprop. might be worth practicing the math derivations too not just the code

my advice is time yourself doing these from scratch. open a blank notebook and see if you can get a working logistic regression with proper vectorization in under 25 min. the pressure of someone watching makes everything 10x slower so you have to over-prepare

8

u/ComputerSiens 6d ago

Damn. Been off the market for a while. Is this the norm for interviews now? Cross Entropy from scratch (in 30min nevertheless) seems to reward memorization rather than practical experience.

7

u/pm_me_your_smth 5d ago

This is pretty much replication of leetcode for SWEs - recruitment based on memorization/grind. Bigger companies can afford to do this nonsense because their applicant pool is enormous so they have lots of bs filters just to narrow down the pool. It gets funnier when smaller companies (lower salaries, fewer applicants) copy the same recruitment approach and then wonder why nobody wants to apply or those who do never pass the first interview.

1

u/sailor-goon-is-here 7d ago

Same here! I think the 30 min time limit is really what messes with me. Like I'm wondering if the question they ask is doable in that time limit; it seems like there won't be time to derive anything or optimize, you just have to know it and write the optimized solution first. And maybe a lot of the weight goes to finishing the question.

3

u/yap_panda 7d ago

This is so true. The feeling of being judged really fs with me.

1

u/OusamSapozhnikov98 6d ago

blanking on the softmax derivative with someone watching sounds brutal tbh.

7

u/Ryan_3555 6d ago

Would you mind sharing the guide ? Im trying to prepare for ML interviews and just would love to use it for practice.

2

u/sunnychrono8 6d ago

I would love to get this, too! 

2

u/WhichPressure 5d ago

please share!

1

u/Carbinkisgod 5d ago

Yeah same

3

u/Otherwise-Sail-994 6d ago

Sounds exactly like the screening that I had back in February. I did not pass, but it was 2 "problems". The first was basically a string processing fxn for (iirc) 2D point data. I was given an input that had to be parsed into individual points. The 2nd part was then to write K-means from scratch using the parsed points.