3 ms·

Becoming a Research Engineer at a Big LLM Lab

55 points by felixdoerp 2mo ago

bluecheese452 2mo ago
The article is somehow even more insufferable than the title.
- deleted 2mo ago
  [deleted]
georgemcbay 2mo ago
tl;dr - the hiring processes in tech get more and more interminable every year.
- vjvjvjvjghv 2mo ago
  I am super happy that I am retiring soon. The hiring process these days just sucks.
baron3dl 2mo ago
[dead]
angarg12 2mo ago
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.
- wordpad 2mo ago
  Were most interviews focused on DSA and System Design still?
  - throwaway219450 2mo ago
    2 years ago, for sure. Every programming interview I had pulled problems from LC. Admittedly it’s quite hard to not, now the database is so big.
  - angarg12 2mo ago
    Mostly yes. But there were also some take home assignments, some culture fit loops, and many ML rounds, since I was applying for an ML role.
indoorfish 2mo ago
"Claude, make a me a blog template, that shows how minimalist I am"
ktallett 2mo ago
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 2mo ago
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.
- vjvjvjvjghv 2mo ago
  How would you define AI? It seems they can do a lot of useful things. They are very good for processing language and I find Claude Code to be a better coder than a lot of human programmers.
  - dosisking 2mo ago
    What I mean to say is that AI encompasses a lot more than just LLM's, and that LLM's in general are a dead-end technology. People think that LLM's are going to keep getting better, but I doubt that they will, they have probably already peaked. In general I consider neural networks to be a dead-end. But they are still considered to be under the AI umbrella. The fact that they hired the guy who wrote the article, confirms to me that there is no substance behind LLM technology. It is a waste of time and energy.
    - vjvjvjvjghv 2mo ago
      Maybe LLM will be to AI what dial up was to the internet. It’s a start that gets things going and attracts investment for better things.
  - wilbur_whateley 2mo ago
    To me, AI is about the ability to solve novel problems. People who think supervised learning can do that usually believe that new knowledge comes from (1) combining old ideas, and (2) trial and error. I don't think that's true. If you think about the state space of all possible ideas, it's clear that humans can explore a very small subset of that space and supervised learning just imitates humans (with great speed and memory). RL also doesn't work, but it at least attempts to learn independently of human knowledge.
conceptme 2mo ago
18 month job hunt is pretty rough, I get that he really wanted this but for most people with "normal" lives outside work this would be a very risky move.
homarp 2mo ago
>A learning hack that worked for me was getting YouTube Premium, which allows for downloads and background play, and then listening to these videos while going for a walk you can also research about youtube-dl/yt-dlp (and using an ad blocker)
throw0101a 2mo ago
I'm not sure why the OP is using that word: he is working for a (for-profit) company, not at a "lab". > Mistral AI SAS (French: [mistʁal]) is a French artificial intelligence (AI) company headquartered in Paris. * https://en.wikipedia.org/wiki/Mistral_AI https://en.wikipedia.org/wiki/Mistral_AI I'm not sure why "lab" is being used for all of these companies in this space. Is it an attempt to sweep their money motivations under the rug, or something else?
- bootwoot 2mo ago
  I don’t think the word lab inherently implies anything about profit motives. Only the focus on frontier research

55 points by felixdoerp 2mo ago

bluecheese452 2mo ago

The article is somehow even more insufferable than the title.

deleted 2mo ago
[deleted]

georgemcbay 2mo ago

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

vjvjvjvjghv 2mo ago
I am super happy that I am retiring soon. The hiring process these days just sucks.

baron3dl 2mo ago

[dead]

angarg12 2mo ago

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.

wordpad 2mo ago
Were most interviews focused on DSA and System Design still?
- throwaway219450 2mo ago
  2 years ago, for sure. Every programming interview I had pulled problems from LC. Admittedly it’s quite hard to not, now the database is so big.
- angarg12 2mo ago
  Mostly yes. But there were also some take home assignments, some culture fit loops, and many ML rounds, since I was applying for an ML role.

indoorfish 2mo ago

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

ktallett 2mo ago

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 2mo ago

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.

vjvjvjvjghv 2mo ago
How would you define AI? It seems they can do a lot of useful things. They are very good for processing language and I find Claude Code to be a better coder than a lot of human programmers.
- dosisking 2mo ago
  What I mean to say is that AI encompasses a lot more than just LLM's, and that LLM's in general are a dead-end technology. People think that LLM's are going to keep getting better, but I doubt that they will, they have probably already peaked. In general I consider neural networks to be a dead-end. But they are still considered to be under the AI umbrella. The fact that they hired the guy who wrote the article, confirms to me that there is no substance behind LLM technology. It is a waste of time and energy.
  - vjvjvjvjghv 2mo ago
    Maybe LLM will be to AI what dial up was to the internet. It’s a start that gets things going and attracts investment for better things.
- wilbur_whateley 2mo ago
  To me, AI is about the ability to solve novel problems. People who think supervised learning can do that usually believe that new knowledge comes from (1) combining old ideas, and (2) trial and error. I don't think that's true. If you think about the state space of all possible ideas, it's clear that humans can explore a very small subset of that space and supervised learning just imitates humans (with great speed and memory). RL also doesn't work, but it at least attempts to learn independently of human knowledge.

conceptme 2mo ago

18 month job hunt is pretty rough, I get that he really wanted this but for most people with "normal" lives outside work this would be a very risky move.

homarp 2mo ago

>A learning hack that worked for me was getting YouTube Premium, which allows for downloads and background play, and then listening to these videos while going for a walk you can also research about youtube-dl/yt-dlp (and using an ad blocker)

throw0101a 2mo ago

I'm not sure why the OP is using that word: he is working for a (for-profit) company, not at a "lab". > Mistral AI SAS (French: [mistʁal]) is a French artificial intelligence (AI) company headquartered in Paris. * https://en.wikipedia.org/wiki/Mistral_AI https://en.wikipedia.org/wiki/Mistral_AI I'm not sure why "lab" is being used for all of these companies in this space. Is it an attempt to sweep their money motivations under the rug, or something else?

bootwoot 2mo ago
I don’t think the word lab inherently implies anything about profit motives. Only the focus on frontier research