Last summer I was interviewing at a FAANG company for a supposed senior level position and I pointed this out.
Instead I was treated as if I fundamentally had no understanding of algorithms whatsoever. It was enormously frustrating, especially when I demonstrated real world runtime to the interviewer of two implementations.
If they need someone to actually make things work well on real physical hardware, they need to know how the claims map to the physical reality and the fundamental limitations of chalkboard optimization. The real world actually matters.
If he knew this maybe he wouldn't be overbudget, overdeadline and trying to mad hire people like some parody of the mythical man month...
8 months later it still rubs me the wrong way - that is, a bad faith read on new information as obviously objectively wrong and the speaker (me) as misinformed even after it's been demonstrated as accurate. Assuming everyone is stupid is a great way to hire, just fantastic.
I'd bet thousands the project is either still off the rails or they've overhauled the org chart.
The product hasn't been publicly announced yet btw.
It's really all for the best. This way I only wasted one day instead of say 6 additional months just spinning wheels against a stonewall.
Of course it isn't. Of course it's a mathematical abstraction.
This project required high performance, high throughout, distributed computing with exabytes of data.
The person applying for the job should illustrate they can deal with that and knows when to ask what kind of question.
If they think chalkboard algo analysis is the end of the game, that they can just pack up and go home, not looking at the actual hardware specifications and capabilities, the real world implementations and costs, and just blindly trust the mathematical abstraction without any type of evidence, analysis, testing, or considerations of a system as complex as the physical hardware they are using, then good luck.
For example, if there is a "slower" implementation that's embarrassingly parallelizable and trivial to distribute, those are actually important factors.
If they have a "slower" implementation that also allows for a quicker mark and sweep or cache invalidation, those are also actually important.
If input data can be tightly characterized, that's actually important, it changes the real world expected results.
Bursty and continuous traffic are different problems so average throughput is insufficient for characterization.
This guy disputed all that. Basically the midterm I took 20 years ago as an undergrad when I 18 at the University, that's it. That's all of HPC.
By the end I was just giving him the college freshman level answers and he was genuinely surprised as if he thought I didn't know it.
Again, last I heard, the project is still on the rocks.
> Instead I was treated as if I fundamentally had no understanding of algorithms whatsoever.
This and similar experiences, basically discovering the interviewer, potential boss, or worse, actual boss, is not a colleague but actually a shallow copy of what one would expect from someone in their role, is pretty common, especially (from what I've seen) in orgs with a clear divide between a "manager" class that is mostly composed of people with less experience than those they are managing, and those doing the work.
It's best, as you say, to just write off the time wasted on the discussion, move on, and be happy you don't have to work with them.
Instead I was treated as if I fundamentally had no understanding of algorithms whatsoever. It was enormously frustrating, especially when I demonstrated real world runtime to the interviewer of two implementations.
If they need someone to actually make things work well on real physical hardware, they need to know how the claims map to the physical reality and the fundamental limitations of chalkboard optimization. The real world actually matters.
If he knew this maybe he wouldn't be overbudget, overdeadline and trying to mad hire people like some parody of the mythical man month...
8 months later it still rubs me the wrong way - that is, a bad faith read on new information as obviously objectively wrong and the speaker (me) as misinformed even after it's been demonstrated as accurate. Assuming everyone is stupid is a great way to hire, just fantastic.
I'd bet thousands the project is either still off the rails or they've overhauled the org chart. The product hasn't been publicly announced yet btw.
It's really all for the best. This way I only wasted one day instead of say 6 additional months just spinning wheels against a stonewall.