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The Machine Learning Job Market

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Re: The Machine Learning Job Market

#131

Post by throw1234651234 »

angarg12 wrote: post #70

I don't want to derail the conversation, but OPs career path really stood out to me. He graduated in 2016, worked at Google in Bay Area, and now is joining a startup at a VP level. I graduated in 2008, obtained a PhD in 2014 in a no name EU university, worked in odd companies for a while and joined FAANG 4 years ago as a mid level developer, where I am still ATM. Looking at this disparity I wonder what could be possi…

If it makes you feel any worse, a fresh-college grad just worked his first month at any job on my team at a midwest company and got an offer at Google making more than I am now. I have over a decade of experience and endless Cloud Architect certs (all 3 clouds) as well as a background in finance.

Right place, right time + talent + willingness to take risk.

Re: The Machine Learning Job Market

#132

Post by visarga »

going_ham wrote: post #71

This post feels like author is insecure about his position and wants to establish some validity. Having going through it all, it feels delusional at best. The glorified pattern matching can only take us so far. You know it's working as long as there is a pattern. I wouldn't call it a general intelligence per se. There is no "juice" in these algorithms. If we use these tools, we can immediately see where they fail and…

> The glorified pattern matching can only take us so far.

This argument is becoming less and less convincing year by the year. We're amazed that things we were sure couldn't be done are actually done.

Re: The Machine Learning Job Market

#133

Post by deep_etcetera »

hervature wrote: post #128
cletus wrote: post #47

Earlier quoted context omitted.

These outliers are rare but they do exist. I knew someone at Google who was hired as L3 straight out of college (as all non-PhDs are) and got promoted once a year to L6 (Staff) so 3 years. He got promoted to L7 2 years after that. It's a rare combination of talent and the right circumstances but it does happen.

I tried to hint at this by using quotes, I don't doubt that L6 is possible. But, please elucidate, are there L6s at Google making "low 7 figures"? From levels.fyi, there are no such reports. The average is about half and matches what I know from other companies. Those that are approaching 7 figures have at least a decade of experience. Anyway, the pay he describes is much closer to L8.

You can see some examples here https://aipaygrad.es/

Re: The Machine Learning Job Market

#134

Post by ChefboyOG »

samhw wrote: post #84
going_ham wrote: post #76

Earlier quoted context omitted.

Yeah, and the way the author presents themselves speaks volume too. There is a real pride in this essay. You can see how the author casually drops big names and insights like it is a fact. Why does valley culture makes it seem like everything is possible and anything innovative can happen soon? The innovation in AI really seems like it is being made on a thin line of engineering and compute. It doesn't happen overnig…

> The innovation in AI really seems like it is being made on a thin line of engineering and compute. This perfectly echoes my own thoughts. The advances being trumpeted in AI are functions of hardware advances that allow us to have massively overparameterised models, models which essentially 'make the map the size of the territory'[0], which is why they only succeed at a narrow class of interpolation problems. And ev…

Eh, if you boil all research in AI/ML down to the binary of "AGI or bust," then sure, everything is a failure.

But, if you look at your smartphone, virtually every popular application the average person uses--Gmail, Uber, Instagram, TikTok, Siri/Google Assistant, Netflix, your camera, and more--all owe huge pieces of their functionality to ML that's only become feasible in the last decade because of the research you're referencing.

Re: The Machine Learning Job Market

#135

Post by falsenine »

As someone whose intention is to go to Medical School and pick up programming (+ math skills) to potentially work at the intersection of ML + Healthcare, the knowledge of the regulatory hurdles expressed is discouraging. Not sure if it really is worth the effort to study tech on top of medicine. Are there any people with experience within ML + Healthcare/Medicine or know of startups that are making great strides within this realm?

Re: The Machine Learning Job Market

#136

Post by mbrameld »

uoaei wrote: post #106
colonelxc wrote: post #73

Earlier quoted context omitted.

In general, yes, I think that would be okay. I think it would be a mistake to create separate sections for each level. Overall your achievements within a single company should not be organized chronologically, but by what you want to show off. This may still be mostly chronological as you take on more responsibility/leadership. Now, I don't object to adding a line like: "promoted twice from Software Engineer 2 to Sta…

But it undeniably misleads the reader into thinking this person has held senior responsibilities since 2016, which is outright false, and may instill in the reader more confidence than is due.

I'll add another data point in opposition. I expect to see only the latest title for each company on a resume and my resume is organized the same way. It's practical, not deceptive.

Re: The Machine Learning Job Market

#137

Post by visarga »

claytonjy wrote: post #11
melling wrote: post #9

Earlier quoted context omitted.

I’m interested in understanding the ML job market for traditional software developers. Does the opportunity exist to transition into any particular ML roles then grow from there?

I've been seeing a lot of Data Engineering/Platform roles that support ML without requiring past ML experience. How much future lateral movement would be available to you will vary widely, but this would be a fairly easy inroad.

You need 3-4 years of intense study to transition from software engineering to ML. It's different enough.

Re: The Machine Learning Job Market

#138

Post by freyr »

angarg12 wrote: post #70

I don't want to derail the conversation, but OPs career path really stood out to me. He graduated in 2016, worked at Google in Bay Area, and now is joining a startup at a VP level. I graduated in 2008, obtained a PhD in 2014 in a no name EU university, worked in odd companies for a while and joined FAANG 4 years ago as a mid level developer, where I am still ATM. Looking at this disparity I wonder what could be possi…

Also, the author grew up in the Bay Area (early exposure to how the SV ecosystem works), went to an Ivy league school (opens doors to top internships), landed those internships, and got a masters. All those things, but especially the internships, can help fast track your early career.

I’d take some things here with a grain of salt, like “low 7 figures compensation (staff level)” at FAAN (can eliminate G because they’re not likely to hire him back at L+1 immediately after he quits). ML is still somewhat hot, but 7 figures is an outlier for staff-level comp.

AAPL: ~$450k https://www.levels.fyi/company/Apple/salaries/Software-Engin...

AMZN: ~$600k https://www.levels.fyi/company/Amazon/salaries/Software-Engi...

FB: ~$600k https://www.levels.fyi/company/Facebook/salaries/Software-En...

Nobody there is reporting $1M+ offers for staff level. While I’m sure it’s happened, it’s pretty far outside the staff pay band (excluding equity gains during the 2020-2021 market run-up, which are sadly behind us) and would be a truly exceptional offer even in the current climate. That, plus the fact that it sounds like he didn’t get many formal offers (“I did not initiate the formal HR interview process with most of them”) and wasn’t pitting offers against each other, makes me skeptical.

Re: The Machine Learning Job Market

#139

Post by bsenftner »

samhw wrote: post #84
going_ham wrote: post #76

Earlier quoted context omitted.

Yeah, and the way the author presents themselves speaks volume too. There is a real pride in this essay. You can see how the author casually drops big names and insights like it is a fact. Why does valley culture makes it seem like everything is possible and anything innovative can happen soon? The innovation in AI really seems like it is being made on a thin line of engineering and compute. It doesn't happen overnig…

> The innovation in AI really seems like it is being made on a thin line of engineering and compute. This perfectly echoes my own thoughts. The advances being trumpeted in AI are functions of hardware advances that allow us to have massively overparameterised models, models which essentially 'make the map the size of the territory'[0], which is why they only succeed at a narrow class of interpolation problems. And ev…

> show me a demo where it answers a hard question whose answer you - all of us - don't already know.

For that, we need artificial comprehension, which we do not. Artificial comprehension, the ability to generalize systems to their base components and then virtually operate those base concepts to define what is possible, to virtual recreate physical working system, virtually improve them, and with those improvements being physically realizable is probably what will finally create AGI. We need a Calculus for pure ideas, not just numbers.

Re: The Machine Learning Job Market

#140

Post by visarga »

rdedev wrote: post #82
PartiallyTyped wrote: post #19

Earlier quoted context omitted.

I think I have a decent CV, with quite a bit of experience for a master's student. I have been searching for a job in MLE, for a bit now with very little to show for it, as I am either getting no responses, or responses claiming that they are looking for more experienced people, and particularly those that had experience with a particular stack. In all honesty, after 6 years of studying, with 4 of those years studyin…

Reading comments like this is a bummer. I am currently doing my masters with a focus on NLP. At this point I'll be pretty happy to get a job even if it just boils down to only deploying ML models. Even for such a role of companies expect years of experience or a PhD I don't know how I can even get a job in the first place

I sometimes interview candidates for ML engineering roles, and let me tell you most of them have trouble with basic concepts. It's great when I find someone fluent, for a change.
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