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Ask HN: Has anyone made the transition from app development to ML/AI work?

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Re: Ask HN: Has anyone made the transition from app development to ML/AI work?

#31

Post by greymalik »

ramesh31 wrote: post #21
LZ_Khan wrote: post #2

From my experience, there are plenty of teams in FANG that will hire you as a backend developer in a ML team assuming you can pass their interviews. 90% of the work in these teams is not core ML and is more mundane work supporting these models, such as data piping, cleaning, feature generation, experimentation, and real-time serving. You'll get plenty of experience in working directly with ML systems. The jump to cor…

>90% of the work in these teams is not core ML and is more mundane work supporting these models, such as data piping, cleaning, feature generation, experimentation, and real-time serving. You'll get plenty of experience in working directly with ML systems. MLOps is what you're describing, and it's probably the number one field I'd recommend someone to go down right now as a backend dev.

Why is that your number one recommendation?

Re: Ask HN: Has anyone made the transition from app development to ML/AI work?

#32

Post by fmxexpress »

I'm a full stack contractor. Been following generative AI since late last year. Picked up an AI startup gig in early January. Launched a couple weeks ago. Building out the client, API, server, and orchestrating the AI image generation pipeline plus Dreambooth. Choosing an AI GPU provider (or 3), solving prompt issues, figuring out model settings, making sure it can scale. A lot of the models are all comoditized on providers like Replicate which makes it like any other API based project. AI knowledge is still very useful to know what settings to use with the models though.

Re: Ask HN: Has anyone made the transition from app development to ML/AI work?

#33

Post by sroussey »

ramesh31 wrote: post #21
LZ_Khan wrote: post #2

From my experience, there are plenty of teams in FANG that will hire you as a backend developer in a ML team assuming you can pass their interviews. 90% of the work in these teams is not core ML and is more mundane work supporting these models, such as data piping, cleaning, feature generation, experimentation, and real-time serving. You'll get plenty of experience in working directly with ML systems. The jump to cor…

>90% of the work in these teams is not core ML and is more mundane work supporting these models, such as data piping, cleaning, feature generation, experimentation, and real-time serving. You'll get plenty of experience in working directly with ML systems. MLOps is what you're describing, and it's probably the number one field I'd recommend someone to go down right now as a backend dev.

This is the #1 thing VC backed startups are trying to automate away

Re: Ask HN: Has anyone made the transition from app development to ML/AI work?

#34

Post by wolterlw »

greymalik wrote: post #31
ramesh31 wrote: post #21

Earlier quoted context omitted.

>90% of the work in these teams is not core ML and is more mundane work supporting these models, such as data piping, cleaning, feature generation, experimentation, and real-time serving. You'll get plenty of experience in working directly with ML systems. MLOps is what you're describing, and it's probably the number one field I'd recommend someone to go down right now as a backend dev.

Why is that your number one recommendation?

because 90% of the industry work is MLOps the pipeline usually goes 1. make a POC inside a Jupyter Notebook with some scrappy, data and off-the-shelf model, define metrics and train a baseline to see if the whole ML endeavour might even be worth it 2. Do error analysis, find better data, tune parameters, re-train to see if you can improve upon the baseline 3. Make the first deployment, setup data collection 4. Automate 2 as much as possible because data is ever changing and you want to try many more off-the-shelf models 5. Deploy new models and collect ever more feedback

4 and 5 are basically a while loop that never ends and that's mostly MLOps It still requires proper ML expertise, especially when things break tho

Re: Ask HN: Has anyone made the transition from app development to ML/AI work?

#35

Post by schmookeeg »

I sort of fell backwards into it about 5 years ago -- in the "Give it to Mike, he'll try anything" sense -- I inherited some mangled Jupyter notebook filled with health data, and nobody could make the model work out. Once I figured out the white paper and algorithm they were trying to rip off, it was easy enough to implement and host out as a PKL file with Fast API.

That's sort of what I've been doing since. It's much more interesting than solving botched up React Hooks, but there is about the same ratio of tedium:interesting work. I happen to like math, someone who does not like math... they're gonna go a little batty I think.

I haven't even raised my rates. I'm having enough fun with it.

So I think the answer you're after is either "Luck" or "Masochistic streak" ? :)

Re: Ask HN: Has anyone made the transition from app development to ML/AI work?

#36

Post by nerdponx »

bilsbie wrote: post #20
LZ_Khan wrote: post #2

From my experience, there are plenty of teams in FANG that will hire you as a backend developer in a ML team assuming you can pass their interviews. 90% of the work in these teams is not core ML and is more mundane work supporting these models, such as data piping, cleaning, feature generation, experimentation, and real-time serving. You'll get plenty of experience in working directly with ML systems. The jump to cor…

What terms would you search for for those first type of jobs?

Can't speak for FAANG, but you can do well at some companies with "ML Developer" or even "Data Engineer" if you have database admin experience and/or are willing to spend time studying up.

Re: Ask HN: Has anyone made the transition from app development to ML/AI work?

#37

Post by bilsbie »

ramesh31 wrote: post #21
LZ_Khan wrote: post #2

From my experience, there are plenty of teams in FANG that will hire you as a backend developer in a ML team assuming you can pass their interviews. 90% of the work in these teams is not core ML and is more mundane work supporting these models, such as data piping, cleaning, feature generation, experimentation, and real-time serving. You'll get plenty of experience in working directly with ML systems. The jump to cor…

>90% of the work in these teams is not core ML and is more mundane work supporting these models, such as data piping, cleaning, feature generation, experimentation, and real-time serving. You'll get plenty of experience in working directly with ML systems. MLOps is what you're describing, and it's probably the number one field I'd recommend someone to go down right now as a backend dev.

Do you literally search for “MLops”?

Re: Ask HN: Has anyone made the transition from app development to ML/AI work?

#38

Post by quickthrower2 »

closeparen wrote: post #25
gardenhedge wrote: post #12

Earlier quoted context omitted.

That sounds like the worst kind of tech position to be in

It's about the same tier as BI dashboards. Huge breadths of data you don't produce but are nevertheless accountable for. All your stakeholders can easily stream-of-consciousness rattle off dozens of new metric/feature ideas or questions about the feature/metric values they're seeing over the course of 45 seconds, each one taking you tens of hours eyeballs deep in SQL to even begin to answer.

A job we would be glad to have replace by an AI for sure

Re: Ask HN: Has anyone made the transition from app development to ML/AI work?

#39

Post by xiaolingxiao »

So I did a lot of ML work in grad school and have also built 4 iOS apps and two web apps. I can tell you building statistical models is not a very interesting grind, it’s mostly cleaning data and fiddling parameters. It’s also unlikely anyone would hire non-stat/math degreed person to do that stuff. On the other hand you’re prob goood at turning models into a. Usable product. Here’s a recent library to do that in NODE https://github.com/transitive-bullshit/scikit-learn-ts
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