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Comment by embedding-shape

15 hours ago

> +1, I have a friend, math PhD that's been working on ML research 5+ years in London yet he has not been able to find any position.

Maybe people simply don't want math PhDs but something else? Since 1-2 years ago I started doing consulting/freelancing in the ML space, but more on the infrastructure, deployments and similar stuff, as a general purpose developer, and I have a waiting list of clients interested in more work, some of them even trying to recruit me to work for them full-time as well. I'm based in continental Europe, fwiw.

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michaelscott  15 hours ago

How've you gone about getting into this btw? I have extensive experience in infra and pipeline rollout but have struggled to find freelance clients for this kind of thing. Would be great to tie it into ML as a learning opportunity there

  • embedding-shape  15 hours ago

    Spent a year of freetime catching up on everything and learning as much as possible, started sharing what I've found works or not, write a bunch of comments on HN and elsewhere, and have a email in your profile, eventually people will find you if you put out good stuff :)

    Also bunch of past workplaces who've adopted AI in various ways who reach out once they find out what my current focus lies, but that's harder for others to replicate unless you've already had a career as a developer.

ballooney  15 hours ago

This only proves the original point which is that there is not much demand for actual machine learning expertise because that is only carried out in a small number of places and what demands there is is for the more basic software carpentry like infrastructure and operations rather than the actual technology and Engineering side of things

  • embedding-shape  15 hours ago

    What parent says about "there are very few available positions" for "engineers that can do real LLM machine-learning" is fair, yeah, I'd agree with this.

    I don't think the "incredibly small minority of companies in the world do any real training or optimisation" part is necessarily as true, as some parts of the work I do get is about helping them optimize training and infrastructure around training. Mind you, none of this is for building LLMs from scratch, it's 99% fine-tuning existing checkpoints.

    I'd also agree with "paulg is in somewhat of a bubble" regardless of this, which is worth remembering whenever you read his content. Same goes for any person living in SF, and dare I say the US. But also, YMMV, I live and work in Europe, probably why I have this perspective.