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Comment by foobiekr | Hacker News Reader

The ML thing would not surprise me at all. ML is so hot that if you know the buzzwords and have done some hello world project, someone will give you a job. It is very much like "html coding" in 1999 and will probably have the same outcome.

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Hard disagree. ML is hard to break into, even with strong credentials. (Source: ML engineer)

I think they probably mean "ML engineering" as in training pre-existing models in jupyter notebooks, the new "data science".

The people that actually create/engineer anything new and useful in ML is <1% of people that "work in ML".

Are those positions real? It feels like once the model didn't work if you did not have the background to know why it wasn't working then you'd be in trouble real quick.

I mean the gap between understanding how to use different models effectively and developing new ones is massive. One is like sophomore year undergrad engineering, the other is like masters/PHD.

And "understanding how to use the models effectively" is being generous for what gets a lot of these people in the door.

I have no idea how these folks find their jobs when many top talents are struggling, but beyond getting in the door as a hire I've seen it get back out the door as a product (ML footgun as a service?).

I don't have any hard numbers on this, but it's not rare.

My company gets an absolute a glut of applicants who did a Boot Camp or even Masters program into science, and rejects most before interviewing. We’re not Google either, in pay or prestige. So I’ll strongly object to your characterization based on extensive anecdotal evidence.

What do you mean by "even Masters program into science"?

A Master’s degree in CS, like a bootcamp, is a negative signal about an applicant.

Why? I did an engineering undergrad and MSCS part time so I could take some fun classes I wished to take in undergrad. What’s the negative signal in general?

Just speculating, but maybe people interpret "Master's degree in CS" as "dropped out of a Ph.D. program because it was too hard"?

The enormous majority of Master’s degrees awarded in most fields are for taught Master’s that bear far more resemblance to undergraduate study than Ph.D. preparation. Unless you know someone has a degree that is only possible to get if you were admitted to a Ph.D. programme the assumption should be that it’s a cat cow. There are exceptions, like GA Tech’s OMSCS, but unless you have excellent reason to believe otherwise an MA or MS can be assumed to be a university’s cash grab.

I'm assuming then that you're talking about someone with a bachelor's degree in something other than CS, but then a master's degree in CS?

> The enormous majority of Master’s degrees awarded in most fields are for taught Master’s that bear far more resemblance to undergraduate study than Ph.D. preparation.

That's a very US-centric assumption that's wrong for Europe, Russia, the better universities in China, India etc. Some masters are 100% research, some 100% taught, some are a mix, some are highly specialized, some are all-round, some are interdisciplinary, some have internships. You're aware of that, right? Not all countries' university systems balance their books by farming foreign MS students in short 100% taught courses. Some of them actually do legit research.

You bring us to a related point: most US recruiters and sourcers, and many programmers, don't know how to evaluate credentials of applicants or institutions from the rest of world, especially the parts that don't speak English as first language. If the applicant is from (say) a 2nd/3rd-tier part of China and did their MS(/BS) there, and unless their parents were rich, raw English fluency is not a very good proxy for subject-matter knowledge, only for their parents' wealth level. I've worked with some brilliant people who didn't come across sounding that competent in interviews, but were great programmers. Many candidates don't sit the GRE/GSAT. (Beware of builtin cultural assumptions and biases in assessing applicants. It took me years to figure out which ones.)

Are you speculating that orzig meant to say "a Master's degree in CS" instead of "even Masters program into science"? Are they somebody you know personally?

> In my experience, an MS degree has been one of the strongest indicators of poor technical interview performance.

> Whereas MS degrees used to be a means for departments to begin vetting future PhD students, I believe that the purpose has, in some ways, shifted to be a cash cow for the university in question.

> Part of the problem is that CS fundamentals instruction tends to happen in undergrad computer science courses.

> One tempting option is to try to get an MS from a top computer science school to legitimize yourself on paper. If you actually are passionate about programming, I would urge you not to do that

https://blog.alinelerner.com/how-different-is-a-b-s-in-compu...

Perhaps you posted this comment on the wrong thread? I'm pretty sure orzig isn't Aline Lerner, because she's the CEO of a recruiting company who used to work in engineering, and orzig says in a recent comment that they are an American engineer. So what could Lerner's viewpoint on MS degrees possibly have to do with unpacking what orzig meant to write when they said "even Masters program into science"?

I notice you haven't answered either of the questions I asked you in my comment, which seems like a pretty hostile attitude to me.

I feel like you're doing the exact same thing the article's complaining about.

Yes, that’s kind of the point. Recruiting is hilariously broken in every industry. Tech is unusually open, transparent and meritocratic. If you can somehow internalise Cracking the Coding Interview or otherwise grind leetcode hard and get an interview you have a good chance at a very well paying job. But there are many, many people chasing those jobs so people use coarse heuristics to winnow down the piles of cvs, among them ranking Bachelors degrees in CS above Masters degrees from the same institutions.

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