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The Machine Learning Job Market

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191–200 of 276 posts

Re: The Machine Learning Job Market

#191

Post by 21723 »

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…

AGI is very unlikely to happen within the next 50 years. Dangerous limited AI exists now and it's going to get worse. I don't worry about malevolent AI, because we don't even know what consciousness is, nor the limits of a (presumably) nonconscious entity's attempts to emulate intelligence.

I worry quite a lot about malevolent humans using enhanced technology (note that most things in technology, once accomplished, cease to be AI) will do. Authoritarian states and employers can already learn things about you (that may or may not be true) that no one should be able to know from a basic Google search. This is going to get worse before it gets better, and if corporate capitalism is still in force 50 years from now, we will never achieve AGI in any case because we will be so much farther along our path to extinction.

Re: The Machine Learning Job Market

#192

Post by 21723 »

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…

AGI is very unlikely to happen within the next 50 years. Dangerous limited AI exists now and it's going to get worse. I don't worry about malevolent AI, because we don't even know what consciousness is, nor the limits of a (presumably) nonconscious entity's attempts to emulate intelligence.

I worry quite a lot about malevolent humans using enhanced technology (note that most things in technology, once accomplished, cease to be AI) will do. Authoritarian states and employers can already learn things about you (that may or may not be true) that no one should be able to know from a basic Google search. This is going to get worse before it gets better, and if corporate capitalism is still in force 50 years from now, we will never achieve AGI in any case because we will be so much farther along our path to extinction.

Re: The Machine Learning Job Market

#193

Post by angarg12 »

axg11 wrote: post #92
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…

Don't despair. I work for a FAANG and have previously worked at startups. Title inflation at startups is a huge factor. In fact, titles are not equivalent between any two companies. I have seen startup CTOs (even series A) transition to senior engineer IC roles at a FAANG. As you identified, location is the next big factor. If you are still in Europe, my advice is to leave or to start your own company there. If you a…

Hey thanks for the comment :)

I'm glad someone validates my belief that "location matters". I moved to the US 2 months ago after 2 years in Covid VISA limbo working remotely for a US team. Settling down has been extremely painful so far but I hope it's worth the effort in the long run.

Re: The Machine Learning Job Market

#194

Post by 21723 »

mysterEFrank wrote: post #146
opensrcken wrote: post #101

The post is not only too braggadocious for my taste, but some of the figures quoted are highly unlikely. I would personally not work for someone with this kind of ego, but there are many such people in positions of power. This article is representative of an attitude I'm seeing around the tech industry, and if this is indeed the level of "confidence" in the Bay, I don't think that's a good sign.

Eric Jang is top ML talent, these numbers are accurate. I work in ML and have followed his work for years

If he's actual top talent as opposed to a poseur who's good at self-promotion, he should stay in academia for his own sake because he'll be crushed in the corporate world. Actual high IQ people get clobbered in corporate, while OKR-ing charlatans climb the ranks effortlessly... yes, even at FAANGs.

Re: The Machine Learning Job Market

#195

Post by titanomachy »

krat0sprakhar wrote: post #130
titanomachy wrote: post #110

Earlier quoted context omitted.

FAANG staff in 5-6 years out of school is not impossible. I know a couple. They are significant outliers in terms of focus, dedication (i.e. hours worked), and raw intelligence. If I had to guess, I'd say 1 in 30 from the population of Google-level engineers.

> They are significant outliers in terms of focus, dedication (i.e. hours worked), and raw intelligence. As someone who has worked at FAANG for 5 years right out of school, getting to staff is less about raw intelligence and more about being lucky with working on projects that did not get canned and finding supportive managers. My friends much smarter than me have not had a good growth purely because they were unluck…

That is true, but one "young staff" I know was initially assigned to a dead-end project. She made it her life's mission to find something more interesting and promotable, and succeeded. But there's definitely luck involved.

Re: The Machine Learning Job Market

#196

Post by 21723 »

marginalia_nu wrote: post #182
water-your-self wrote: post #162

Earlier quoted context omitted.

He claims to be solving general intelligence in 20 years. Your advocacy is not enough to convince me.

General intelligence has been 20 years away since the 60s, along with fusion power and a bunch of other things. In marketing, they say 5 years when it's actually 20 years away.

In my view, AGI is farther away than fusion.

We know how to do fusion. We know the physics behind it. We haven't yet figured out how to build profitable fusion plants, and we probably won't for a long time, if for no other reason than improvements in fission--modern fission plants are the best .

When it comes to AGI, we have no clue. It's a constantly moving target, because our conceptions of intelligence evolve. Most things that were once "AI" became "non-AI" solved problems after we got good at them using a couple key insights, e.g. that image processing could be sped up with CNNs due to the existence of a topology on the inputs. We still have no idea what makes us tick, and moreover there is not a strong economic incentive to replicate all of our intelligence... although, of course, automation will continue and that itself will be disruptive enough.

Re: The Machine Learning Job Market

#197

Post by sigmoid10 »

fxtentacle wrote: post #183
rychco wrote: post #65

Earlier quoted context omitted.

This has become increasingly important to me too. I am employed by a small (2-4 engineers at any time) company and I'm often disappointed because we're just so far behind in manpower & technical expertise that we have to dramatically reduce the scope of any problem we want to tackle. On the other hand, I also worry about getting sucked into the bureaucracy of FAANG sized companies & not having any accountability or a…

I'm surprised. Apart from DALLE, I haven't seen any AI approach that's off limits for 4 highly motivated people with 3090 GPUs. At that compute level, you should be able to at least replicate SOTA in optical flow, structure from motion, speech recognition, text to speech, translation, text summary, sentiment analysis, image classifications, image segmentation, and of course playing video games or optimizing processes…

Pretty much everything in the high end large language model area is off limits to people without access to a supercomputer (we're talking hundreds of A100s or several $100k in cloud computing equivalent). Open Source efforts like BigScience may open up downstream tasks for normal people, but the forefront of this research is no longer accessible to individuals.

Re: The Machine Learning Job Market

#198

Post by 21723 »

1024core wrote: post #26

"FAANG+similar : Low 7 figures compensation (staff level), technological lead on compute (~10 yr)" I don't know where OP is getting these figures from, but I doubt that FAANGs offer 7-figure comps to Staff-level people. It's probably more in the higher 6-figure level (400K - 600K).

They're paying for a mascot. It's a marketing expense. $1.2 million per year is nothing when one considers the increased ease of hiring young grunts who do the ugly but necessary work, and who do it well because they think that if they pay their dues, they'll be picked to do the upper-caste "interesting" work, which of course they won't.

In those jobs, you don't even have to show up (although most of themdo, in order to stay relevant but also because these ex-academics tend to be very driven people). You're getting paid well for letting the company say you work there, because this makes it easier for the rest of the company to fill out their chain gangs of early-20s Jira jockeys who'll be used for three years and then PIP-raped because "yellow zone".

Re: The Machine Learning Job Market

#199

Post by 21723 »

rakejake wrote: post #74
georgeburdell wrote: post #40

Earlier quoted context omitted.

That was my pre-conception as well. I know some people who have tried to switch from other engineering to ML/AI, some taking as much as a year off work, and the only successful ones already had a network in the Bay Area from their previous associations (prestigious university/employer).

Yep, at that level, there is a ton of competition. The self-driving industry is almost like the video game industry and actually has a ton of employees who previously worked in video games. They are definitely much better compensated in ADAS but the work culture is similar (anecdotally so YMMV). ML is the sexy wing of the tech industry, so it tends to attract the people who are willing to put in the hours (for interv…

This is because there isn't really much demand for genuinely innovative ML in the tech world. It's a third-circle nice-to-have, not part of the core business.

It enables the business to say they invest in R&D (tax writeoffs, marketing) and it also makes it easier to hire the grunts who'll do the scut work, thinking they'll one day be working on something more interesting (which they won't be).

Competition for bullshit "data science" jobs isn't that tight. For genuine research that actually matters, it is, and that's because most of these positions exist as recruiting tools (you're getting paid to let the company say you work there) and that's always going to be a thin ledge to try to perch on.

Re: The Machine Learning Job Market

#200

Post by 21723 »

visarga wrote: post #140
rdedev wrote: post #82

Earlier quoted context omitted.

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.

All these fields have that problem. There are people who are great at aping the signals (and even beating publication metrics) but really don't know anything. When they show up on a job, they get put into a PM (or actual management) role to limit the damage they can do. They learn enough lingo to be able to convince 90% of people they know what they're talking about (congrats on being in that other 10%, though) and will move up forever. Meanwhile, people who actually know their shit are usually too busy actually being smart to play the games necessary to get themselves hired in a hyper-competitive job market. So it goes.
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