Submitted by diffusion-xgb t3_ysc7gs in MachineLearning
Hi,
We all have heard about the layoffs in tech companies. How about ML/AI jobs? Do you observe a decrease in the number of job openings etc?
I am a bit confused because there are so many AI startups now announcing getting funded. Someone in the industry who has more experience can maybe shed some light?
This is the correct reply. Unfortunately when things get tough, you need to get close to revenue. AI and data science roles are typically not that, especially speaking from personal experience. Same goes for things like cyber security or even managerial (you only need so many managers). The best skills you can have right now are applied SWE skills IMO.
Ads ranking and recommender systems seem safe bets for being close to the revenue.
Yes, you are right, recommender systems may be the exception.
If a big company which main business is not ML related, but use ML to reduce costs and improve. will probably don’t reduce the budget. In my opinion all sectors will be affected but IT will remain stable almost our corporations an new startups invested a lot and what they are looking is to estabilize and improve their numbers.
but isnt most IT only 'value adding' and therefore not essential? i mean you only need ops to keep the lights on, right?
SWE is not IT
Then how exactly is SWE categorised as?
As swe
IT is pretty essential to the operation of any company. Things like workstations, printers, office networking, email, and application servers.
I was being sarcastic, I myself work in IT
Twitter layoffs are because of the Elon shitshow
Meta layoffs are because their stock is crashing, because their business strategy isn't as strong as it used to be.
As far as I'm aware those are the only significant outliers in terms of layoffs.
ML market is still great. And half of the exciting work in ML is coming out of startups.
Also ML was one of the less impacted from what I heard in Meta.
Twitter is an Elon shitshow. Thats a special case as you point out.
I was chatting with a Meta recruiter during their hiring freeze (before layoffs) and they told me that MLEs were the only job category they were still actively hiring for.
Weird, I was also chatting with a recruiter from Meta specialized in ML and she told me they were freezing all hires. It may depend on the groups
It might also be different time periods. I talked to them a couple mos ago, at the beginning of all the tech hiring freezes
Yep, same here. An internal recruiter reached out to me by email and on the call said that everything was frozen except for backend and ML engineering. This was I think in August or September.
Afaik ML was impacted, but mostly responsibility folks getting booted in Meta.
> As far as I'm aware those are the only significant outliers in terms of layoffs.
Not really. https://layoffs.fyi has a good overview of layoff stats and there are many more companies that are contributing to this wave.
FYI, those include layoffs of any kind, e.g. Hello Fresh layoffs of 611 were all warehouse workers, according to the linked article.
It's hard to get specifics about layoffs for software and ML type jobs.
What? Your own source there shows that the number of companies "contributing to this wave" has been steadily decreasing month-on-month, and November's numbers are looking to be on par with the Summer in terms of number of companies. So yeah.. not a trend in unusual layoff numbers.
And if you omit the outliers of Meta and Twitter, the overall numbers of layoffs from the industry look to be completely on trend, aside from those specific outliers.
The data itself shows that we aren't in that big layoff wave yet.
Twitter and Meta are the most visible examples but they aren’t outliers as far as layoffs go.
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How much ML does twitter actually do?
Meta is crashing because Apple fucked them
Meta is crashing because of C level hubris and the belief that they could be the central point of all social interaction online and in the metaverse. They've been making poor decisions internally for years and its catching up to them.
They’re crashing because they got fucked by Apple on targeted ads (their cash cow). They put themselves in a position to get fucked by Apple because so far they failed to become an OS/hardware company.
Why do you think they’re pushing for VR? To push the adoption of Oculus headsets. They failed with the Facebook Phone so now they’re thinking : whats the successor of smartphones ? VR headsets. It’s why Microsoft is betting on it as well
It’s a rational decision. Execution is another issue though
how so?
They stopped Facebook from tracking users on iPhones. Basically making their targeted ads on iPhones (most of their revenue) shitty. Apple is selling this as a privacy measure, but we all know they’re gonna start doing targeted ads themselves
privacy-conscious targeted ads. iAds.
ah got it
This is one of the only factual comments in this thread. ML and data science are the future of technology. This becomes apparent if you take the time to analyze almost any consumer tech product and realize it's likely backed by some sort ML or AI.
Snap had a huge one too, I have no idea why though I just see them in my candidate pipeline.
Totally agreed
What about the Stripe, Lyft, Zendesk, Redfin layoffs??
Meta feels like they are preparing to pivot away from that "meta verse" plan. Feels like the 90s called and asked to get their impractical VR worlds back
There is a lot of uncertainty out there for sure. I know people who've done multiple internships with the same company over the course of their PhD and are worried they might not receive a full-time offer when they graduate. I'm not sure if their concerns are founded or not, but that's their current outlook.
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Ah that really sucks to hear
It is true for Meta, most of the research interns didn't get return offers. Amazon on the other hand is dolling out AS offers to everybody. Everyone on my team at AWS got a return offer
This definitely depends on the org then. I did not get an AS return offer because of head count/the hiring freeze. Still a bit upset :(
Funding in ML is down ~80% this economic downturn. It’ll be back but it’s tight right now
Source?
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That's just VC funding though, right? There's still a ton of investment from the big co's
Doesn't this say -~30%, not 80%? What am I reading wrong here?
The big opportunities right now are in the Hypergrowing Startups that have raised tons of money, there's a next gen wave a foot and this is the time to get in on the next big company. The FAANG companies are all going the way of IBM this cycle and won't be the hyper innovators of 10 years ago, so find something cool, new, hip, and fresh and go for it
yeah right, Microsoft totally missed cloud ... or AI ... or VR ... or ... actually, what did Microsoft miss except for mobile?
The web?
It’s not that hey missed it. It’s more that they’re shedding jobs, freezing hiring so it’s harder to get in and you’ve got more competition
Bill Gates wanted to create his own closed Internet if you were around in 1994 …
This is the dumbest fucking thing I've ever read
You mean the Hypergrowing Startups that now have to deal with constricted capital from skyrocketing interest rate hikes to curb inflation?
Jasper Ai, stability AI, cohere AI, are all raising hundreds of millions in funding and are the future, you’ve got actors like mid journey who’ve got a lot of traction so you gotta look at the new wave
Would you still give this advice to a graduate? I just finished a Masters in Artificial Intelligence, and I worry startups aren't the best place to grow my skills for industry?
The worlds changed over night,the big players are all on the layoff train and gotta cut jobs to jump that stock while a startup is riskier, it’s what’s the future. Sure you could try and go to a bigger company, but how are you planning to get in when they’ve cut like 10 - 15% of the workforce?
Startups aren’t usually the best place to go for the first job unless they have good mentorship infrastructure (some do, most don’t). And I say this as someone who has spent half of their career in startups and loves startupland. Make sure you suss that out while interviewing.
IBM's quantum computing is getting more fascinating dont know if quantum ML will be the next big thing.
Depends on application, companies in which ML is part of the main product will be more robust, experimental/research/marketing will probably see more issues, data scientists who aren't already operational with proven numbers might take a large hit
I think you have to bear in mind that MAANG exists in a different sphere than tech or AI/ML in general. There are plenty of companies who have a need for it, and that won’t change just because MAANG is getting rid of bloat. That said, jobs will probably get at least a bit more competitive because people being laid off will be looking for jobs.
“A bit more competitive” is an understatement. There’s an increased supply of workers and an increasing number of them are lowering the expectations about compensation. Companies that are hiring will have many options, and they’ll likely chose the option that costs them less.
Source?
Ask your friends who were laid off at Meta, in the past couple months, who is hiring them with the same compensation they were getting at Meta, or better.
Big companies are firing more non-essential members of the team. Also, research & unreliable money makers get cut first.
So it makes sense that SWEs don't get fired because they maintain the systems. On the other hand, a lot of AI products are not making a shit ton of money just yet, the research costs are very high and the AI Scientists don't usually do the job of maintaining an AI service.
So they get fired with a higher priority than SWEs.
Now, in a downturn, cost cutting takes major priority.
Those 4 things have made it a rather decent time to be in an ML startup, but not so great time to be in ML at a bigtech company.
3: Yeah but you gotta raise muney. Muney harder to raise in tough markets.
AFAIK, There aren't a lot of series A or seed rounds happening.
But pre-established startups like Jasper are getting funded because premier investors have already invested a ton into them. In for a penny, in for a pound.
Overall volume is down but deals are happening. My company just closed our series A and later stage VCs with money to deploy are retreating to earlier stages like seed and series A.
I work at a AI series C company and we had layoffs on march and freeze hiring. Board told leadership to adjust the burn rate to last 2-3 years.
Original plan was to get funding next year. So, yes, market reached peak early this year and most companies are adjusting for at least 2 years down turn.
I only see one example in your post of adjusting for such a slow burn rate. Might be a good strategy but I’m not sure most startups (especially earlier stages) are doing this, at least not yet.
Purely conjecture but I get the impression it's just some correction for the insane bloat in big tech, particularly after the covid tech bubble. Meaningful work on meaningful problems is not going away and will continue to grow. I think companies are just (rightfully) reconsidering their priorities a bit.
Seems that the academia tangential AI research openings are going to be virtually non-existent for the near future, and existing jobs may be at risk.
Those that are closer to the direct value chain (i.e. a data scientist who can point to their A/B test increasing revenue by $X) are going to be safer until the market is on another upswing.
I might be wrong but I’ve seen a growth for data engineers these past months. But I’m not sure it’s a trend specific to my country.
ml gives companies a competitive advantage in a tough market. There will be churn for sure but if anything there are and will continue to be more demand than supply in the space, just maybe not as much of a gap.
Market's about to be flooded with a bunch of utterly useless social media programmers.
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Most ML use cases are R&D and improvements to existing performance. When funding issue comes, ML can be cut and replaced with heuristic rules with a trade off in reduced performance.
Unless you're working in a very niche ML application, you're not really needed to keep a company operational
> ML can be cut and replaced with heuristic rules with a trade off in reduced performance.
Then it all depends on what was more expensive - the ML team or the trade-off.
ML is a snakeoil business
I had been recently laid off but I was also the last who joined the team. Kinda sucks because I just left my old job for that. This company depended merely on ad revenue and I knew that such employers mean risky business, since they put all their eggs into the same basket. The current recession showed that advertisment is the first thing where spendings are cut short.
I work at a FAANG and seeing some accurate and some inaccurate things here.
Overall, AI is seen as a key factor to success against competition. AI driven ranking changes can be incredibly impactful in the right context and the downstream ROI tremendous.
ML Engineering jobs are still incredibly sought after.
Pure research might be a different story due to lack of ROI. But research that can be incorporated and applied to product will be seen as valuable because of point 1.
Any company that needs to do stuff at scale will likely need to use ML. Looking at Twitter for example shows a lot of opportunity for ML (spam, abuse detection, feed ranking).
The future of ML jobs is incredibly bright and only going to grow from here.
Wait what, Twitter's hiring again? They literally just laid off entire divisions a week ago, which included a lot of ML teams from what I read.
No, I wasn’t saying they were hiring. I was saying their products would benefit a lot from deploying more ML.
Oh, ok well Musk holds the exact opposite view as a general rule[1] and a guy I follow on Twitter who was a Senior ML engineer in one of the content teams there was laid off, and he's not the only one from his team let go either.
While you've picked a great example from a technical perspective, company wise it's the last place where I'll expect any expansion of ML funding/budget over the next year unless Elon hires somebody else to be CEO.
He says unless you have to use ML, don't do it. I see no other way to detect spam for example other than ML.
Well I'm on this sub and ML is my job so I obviously see that and I agree but as a thought experiment consider this- if you basically paywall Twitter/get rid of the feed curation entirely it's already going to have some sort of spam reducing effect.
With where he's going with the verification process and his previous rant about bots I think something that'll soon be Twitter is what 2010 Facebook was like - you only see content from people you friend and only they can see your posts unless you want to take the risk of opening up to the public. Only way to make this model profitable though is the $8 fee to absorb the impact of not showing ads in the feed, and if a critical mass of your users sign up you can make all posts "verified only".
Not saying you can solve a hard problem like spam without ML, but you can greatly reduce the noticeability of spam if you don't let anybody interact with anybody else without their explicit consent.
The downstream effect this has is you can invest 1/10th the budget you originally had to fight spam and still not have your platform go down the gutter.
I mean this is just speculation but I don't think that the spam rn is happening because Twitter is free. It's because it's profitable and as long as it's profitable it will happen. The only way I think Twitter can reduce spam by asking for user verification.
ML also has the benefit of scaling well. If you build a ML system to detect spam, I wouldn't say there's much difference in development costs if you 10x the user base and I do not see Twitter not having such a ML system. The model isn't going to be 1/10 as cheaper to train and the size of the engineering team isn't going to be 1/10 too.
As per ML in general, I doubt we are going to see a decline, all these layoffs in big tech and ML teams are basically the only ones that are still hiring over the board. I think that's it is pretty clear that investment in ML saves money by now, it can automate processes for a fraction of the cost. My experience is only in research tho, so I'd like to hear your thoughts on this.
Let’s see. Obviously ML is a core part of Tesla and he’s said in the past he sees it as a key to fixing Twitter. I wouldn’t read too much into his current cuts because he’s also just trying to cut what he perceives is dead weight. Maybe the guy who was cut wasn’t shipping.
Yeaah, I was thinking about changing jobs but with the current situation I decided it's probably just best to hunker down unless I see something I really like.
I've been doing ML work for the government in a research position. I've been trying to break out and get into commercial ML, but not having CI/CD and cloud experience is basically gatekeeping me. I can't get away from the military and into green tech no matter what I do. Very frustrating.
> but not having CI/CD and cloud experience is basically gatekeeping me
Big tech doesn't really care about this. Are you passing leetcode & ML skills screens? This is where I would focus.
(Well, would have, prior to the current crash...)
Eh, I've had 3 interviews so far and that's what they want. I've got lots of experience with data wrangling, model development, etc, but I keep hitting that wall of, "we use AWS and need someone to help with the production side of things."
I'm signed up for a lot of training courses, specifically GCS and AWS, so maybe I'll have more luck once I've completed them. There's still the issue of getting practical experience, but I'll figure it out at some point.
> but I keep hitting that wall of, "we use AWS and need someone to help with the production side of things."
That doesn't sound like big tech?--Meta, Alphabet, etc. heavily use their own internal tools.
> but I keep hitting that wall of, "we use AWS and need someone to help with the production side of things."
Also doesn't sound like "truly" ML roles.
Not really aiming at big tech. I guess I should have clarified that, my mistake. If you know MLOps, you know stuff like Apache Spark, Databricks, etc are part of the ML pipeline. I agree, it isn't very ML, but that's what they keep asking for.
Yes, understood--you're aiming at the wrong market, is what I was trying to get at.
I guess I'm just not sure where my market is. This job was literally called "Machine Learning Engineer," and their description had all the things I was looking for. Not sure if it was a bait and switch or if I need to be looking for certain terms or job titles.
Sounds like you are looking more for a role advertised with more of an R&D role--"data scientist", "ML research engineer", etc.
Role names are fluid/arbitrary, but "ML Engineer" at anywhere other than the largest shops (or very AI-specialized startups) is generally going to be someone who can help get an ML system into production (hence the cloud concerns).
Your general options (other than somehow boning up on cloud and passing the interviews now) would be to more narrowly tailor the roles you apply for (per above); continue to apply for MLE but be aware of the issues (per above); and/or apply to some general SWE roles so that you can get some more modern commercial/cloud stack experience.
As a general statement, 1-2 years of a generic SWE role would probably do wonders for your infrastructure-level knowledge; i.e., you'll probably be able to write your own ticket after this.
That said, if you have zero interest in expanding into this, I'd just focus on applying roles that are more narrowly written.
That's some good advice. I'm more interested in doing similar work in a green tech field, so I guess I'll focus more on the SWE skills. I don't necessarily want to limit the scope of what I apply to just yet. I'm sure if I poke around and pretend like I can't do my job otherwise, I can get some funding allocated to an IRAD project just for me. Should be able to swing a "mock cloud infrastructure for future ML/AI development." Plus, it'll probably help them out in the long run. The gov is both incredibly long and short sighted sometimes. "We want AI, it's the future, we want to invest in it for the next two decades" along with "wait, you need computers to do AI?"
I'm not excited about staying where I am for that long, but that whole "write your own ticket" part might be worth the time.
CI/CD?
Continuous Integration / Continuous Delivery
I have 4 open headcount right now (am). The layoffs and slowdown has mostly been in big tech companies from what I have seen, traditional companies are still heavily hiring for ml.
ML is a bit like „throw things at the wall and see what sticks“, this could be one of the first things that companies are going to stop when the need for saving arises, because this procedure generates a lot of waste.
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I’d say overall volume of my inbound recruiter messages is down, but I straddle a few different job titles and the ML ones are still going pretty strong.
My employer just recently closed our own series A, and a lot of AI startups are still being funded (we also have a good ARR for our stage) even though the overall environment is more difficult. I think a lot of rounds are closing now too as VCs prepare for the quiet holiday season.
The types of teams that are being affected seem to be teams overly invested in research with no direct path to product, Amazon just laid off a bunch from Amazon robotics, Amazon AMP, ethical AI in meta/twitter. 2023 will probably squeeze us further, so if you work in a team that has very expensive models that don't have a good ROI, those would be the first to go
Good question -- Banking, Insurance, Core ML, which help businesses would remain.
Do anyone here have friends at Google Search Team?
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ok531441 t1_ivyc8oo wrote
It’s normal to have more layoffs, many ML jobs aren’t essential. We’re still hiring but most people we’re interviewing have been recently laid from somewhere so the market has definitely been impacted.