Becoming a Research Engineer at a Big LLM Lab

bluecheese452

The article is somehow even more insufferable than the title.

georgemcbay

tl;dr - the hiring processes in tech get more and more interminable every year.

angarg12

My last job search 2 years ago took me 9 months of grinding while working full time at Big Tech and +15 years of experience. After loops with ~30 companies I ended up with about 6 offers. The offers were all over the shop. Some places downleveled me to mid level while others upleveled me. The comp range was about 3x between the lowest and the highest. Also I couldn't find much of a pattern on the processes and outcomes. No name companies rejected my application without even a phone screen. Lower tier companies offered me lower levels while famously hard to crack ones offered me higher levels. I also didn't see much correlation on how hard interviews were. I'm totally convinced the job market is a numbers game and there is a high degree of randomness and luck involved. Discipline and hard work help, but outcomes are far from guaranteed. Last time I almost didn't leave my job since most offers were worse than my then current one, until I got 2 high quality offers at the end. I have only skimmed through the article but I'm impressed OP got a job as a Research Engineer with no formal background, given that I got doors slammed even after PhD + years of relevant experience. I don't want to diminish the accomplishment, but I would be very wary of anecdata and formulas for success. OP quit his job and focused 100% on the search, and it paid off. I know many more similar stories that didn't pan out, and people had to rush to get lower quality jobs or, in the worst cases, got into long term unemployment. Just my 2 cents.

indoorfish

"Claude, make a me a blog template, that shows how minimalist I am"

ktallett

I'm slightly questioning the term "guide". Basically you have said become a possibly useful researcher in Machine Learning by learning about machine learning, and because Machine Learning takes place on computers it's useful to know how they work too. This is the equivalent of me saying, if you want to join me researching quantum computing. You need to learn about the quantum and then the computing. Broadly at first then choose a niche. It's a bit, well obviously.

dosisking

This article is why I see LLM's as a dead end and not real AI. LLM's are somewhat useful for things related to language. LLM's are a decent search engine. But LLM's are not AI.