With the advent of LLMs, multimodality and “general purpose” AIs which seat on unimaginable amounts money, computing power and data. I’m graduating and want to start a PHD, but feel quite disheartened given the huge results obtained simply by “brute-forcing” and by the ever-growing hype in machine learning that could result in a bubble of data scientists, ML researchers and so on.
The bubble is already there. Since the end of the pandemic, huge layoffs happenend in the ML department and the market is flooded with job-seekers right now.
My friend’s startup - a small no-name ML startup that pays 50k canadian dollars a year - has posted a job offer recently and received more than 1000 applications in 2 days.
But surely not 1000 PhDs?
Actually he told me they got many PhDs from non-relevant fields like biology etc.
Why are ml departments laying off?
I am not sure, I work in academia and we didn’t have this problem.
I suppose it is the backlash from the hype that started in 2015 when random companies started hiring data science teams and later realized they didn’t need them, but most notably the big tech companies fired many ML people at the end of the pandemic, which flooded the market with highly-skilled job-seekers and made it hard for newcomers up to this day, as far as I have been told.
Well guess it’s not only laid off people but just everyone and their dog wants into the field. We also had one ML job listed and got tons of CVs (not thousands, more like 200 even though we’re a public company with remote first and pay for the role more in the 150-200k US$ range).
There was really everything there, from carpenters who studied physics 10 years ago over accountants up to a guy with 20 YoE on everything from spaceships to submarines.
But yeah definitely much more qualified folks than for developer roles. Quite a few I would have hired if I could have