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Ask HN: How to Break into AI Engineering

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Re: Ask HN: How to Break into AI Engineering

#61

Post by electrondood »

dragonmouse wrote: post #58
electrondood wrote: post #24

Can you elaborate on what "AI engineer" means to you?

I left the question a bit open ended to see the diversity of the field and to hopefully gather advice that could benefit others as well. That said, primarily _for me_ it's more defined in what it doesn't mean - Which is software engineering _using_ AI (eg - LLMs) and prompt engineering. I'm already a self-taught web/mobile developer with 10+ years experience, and have built some toy projects using LLMs and image diff…

Got it, thx for clarification. I think you're asking how to move into data science.

Re: Ask HN: How to Break into AI Engineering

#62

Post by lurker919 »

hcks wrote: post #14
nikhizzle wrote: post #3

Assuming you have the math and algorithmic background, I would start by reading the “attention is all you need” paper. After reading, attempt to build a baby transformer model in PyTorch. After that, consider constructing some of the building blocks without libraries to understand how they work.

I read this exact advice often here on HN and I can’t help but wonder. Is the person writing it just repeating something they read? Is it just because they like the ´coding from first principles’ aesthetics? I mean let’s imagine that someone does read that paper, and manage to replicate the code (quite an effort from someone coming from outside AI and academia). Then what? I doubt it’s particularly illuminating. That…

> That doesn’t really qualify for a job by itself

Apple often asks it's ML engineering candidates to explain attention & transformers from scratch.

Re: Ask HN: How to Break into AI Engineering

#63

Post by usgroup »

I think studying what happened to the “data engineer” role is a good indicator.

There was a brief moment in time wherein data engineers were computer scientists specialised in distributed systems and data processing algorithms on commodity hardware. You had to know a lot on average.

Then came commoditisation via the big vendors and now you really don’t need to know very much. As a result it is not uncommon to meet “senior” data engineers who mostly script Python, do SQL and configure Airflow.

I think ML ala AI has already gone that way and many vendors are strongly promoting developer participation with courses and plug-and-play resources.

So what do you need? A vendor certificate you took over a weekend, and an employer to say “yes”…

Re: Ask HN: How to Break into AI Engineering

#64

Post by jahsome »

flashgordon wrote: post #52
jahsome wrote: post #33

Earlier quoted context omitted.

Highjacking for self-edification as you led with math... Is math going to become more important for software engineers in general, as AI is adopted in to more and more aspects of the SDLC, even if said engineers aren't working directly on the AI systems themselves? I ask because I'm quite math averse (dyscalulia). I am self-taught engineer, largely because it became glaringly obvious I wasn't going to be able to comp…

Til I learnt about discalulia!! Interesting. I know math can cause anxiety in kids as/when there is an external "reward/loss" contingent on it. I wonder if that exists when those external incentives are removed? I did a ee and cs degree in college and I hated the eng part of it. It was because I hated the exams which was mostly rote stuff. When I finished college though and started working in a job that had no linkag…

I have attempted a couple times to re-learn and the result is always the same. It goes beyond anxiety. If I try to read so much as a three digit number, my brain turns to mush and things start to get blurry. I have trouble reading ticket numbers on a daily basis, and struggle to help my grade school kids with their homework. I _can_ do formulae and calculations when I really hunker down, but it takes me considerable time, and I'm often wrong.

Re: Ask HN: How to Break into AI Engineering

#65

Post by jstx1 »

usgroup wrote: post #63

I think studying what happened to the “data engineer” role is a good indicator. There was a brief moment in time wherein data engineers were computer scientists specialised in distributed systems and data processing algorithms on commodity hardware. You had to know a lot on average. Then came commoditisation via the big vendors and now you really don’t need to know very much. As a result it is not uncommon to meet “s…

> an employer to say “yes”…

This is a "just draw the owl" kind of comment. It's hard to get hired with just a certificate for plug and play tools and it isn't the kind of job OP wants anyway.

Re: Ask HN: How to Break into AI Engineering

#66

Post by usgroup »

jstx1 wrote: post #65
usgroup wrote: post #63

I think studying what happened to the “data engineer” role is a good indicator. There was a brief moment in time wherein data engineers were computer scientists specialised in distributed systems and data processing algorithms on commodity hardware. You had to know a lot on average. Then came commoditisation via the big vendors and now you really don’t need to know very much. As a result it is not uncommon to meet “s…

> an employer to say “yes”… This is a "just draw the owl" kind of comment. It's hard to get hired with just a certificate for plug and play tools and it isn't the kind of job OP wants anyway.

I wasn’t commenting on how difficult it is to be hired —- that’s relative to many things. But in terms of the least you need, I think I’m unfortunately right because I have seen it many times over the least few years.

We will see over the next few years when every 2nd BI analyst has become a AI engineer :-)

Re: Ask HN: How to Break into AI Engineering

#67

Post by gremlinsinc »

dragonmouse wrote: post #58
electrondood wrote: post #24

Can you elaborate on what "AI engineer" means to you?

I left the question a bit open ended to see the diversity of the field and to hopefully gather advice that could benefit others as well. That said, primarily _for me_ it's more defined in what it doesn't mean - Which is software engineering _using_ AI (eg - LLMs) and prompt engineering. I'm already a self-taught web/mobile developer with 10+ years experience, and have built some toy projects using LLMs and image diff…

there's ml, which requires math. lots of it, for the rest of us there's so much we can build now by just interfacing with language models using tools like langchain or llama index.

The future of ai, is models so advance only an ai can understand or create them, and they will do just that I'm a feedback loop of sorts.

Re: Ask HN: How to Break into AI Engineering

#69

Post by areyoukillingm3 »

janalsncm wrote: post #17
hcks wrote: post #14

Earlier quoted context omitted.

I read this exact advice often here on HN and I can’t help but wonder. Is the person writing it just repeating something they read? Is it just because they like the ´coding from first principles’ aesthetics? I mean let’s imagine that someone does read that paper, and manage to replicate the code (quite an effort from someone coming from outside AI and academia). Then what? I doubt it’s particularly illuminating. That…

I’m an ML engineer and frankly that paper is not very good in my opinion. It’s quite confusing. The BERT paper is much more approachable.

Could you post a link to "the BERT paper"? I've read some, but would be interested reading anything that anyone considered definitive :) Is it this one? "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding" :https://arxiv.org/abs/1810.04805
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