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Ask HN: What is the outlook for a new career in ML or DS?

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Re: Ask HN: What is the outlook for a new career in ML or DS?

#11

Post by cloudsec9 »

People who can predict things will ALWAYS be in demand, especially in Marketing and Sales. ML & DS aren't perfect predictions, but with good math and good data you can be right a lot.

What I'd say is since everyone is shedding employees that the next 6 months - year or longer, however long the recession is bad lasts, will be bad for all tech people. But as the economy improves and the recession recedes, good companies are going to want to know where to spend money to capture that growing market.

Re: Ask HN: What is the outlook for a new career in ML or DS?

#12

Post by lytefm »

yold__ wrote: post #10
greatpostman wrote: post #8

My experience is that it’s a winner take all field. A small minority of candidates receive huge compensation. They have good degrees and publications. Generally they make 25-50% more than a similar level vanilla software engineer. This is especially the case at top tech companies. If you aren’t one of those, being a regular swe is much better. A lot of ml roles are using canned models, and increasingly so. Many data…

> Generally they make 25-50% more than a similar level vanilla software engineer. It's often even less in my experience. Despite having a "unicorn" skillset (soft-skills, advanced degree, domain experience, and SWE experience), I make about as much as a vanilla SWE. There are a huge number of inexperienced PhDs that want into the field, and we are flooded with resumes every time a DS leaves. Also, most of the time, m…

> Also, most of the time, models don't really matter. What makes or breaks most DS projects is soft-skills, stakeholder management, and data cleaning / feature engineering.

I have the same impression. I did my Master's degree in data science, but I quickly realized that coming up with ideas and running the models is the easy part. Doing the engineering work + synthesizing everything such that value creation occurs is more difficult.

I'm happily doing mostly data engineering + stakeholder management instead of hyperparameter tuning.

Re: Ask HN: What is the outlook for a new career in ML or DS?

#13

Post by greatpostman »

yold__ wrote: post #10
greatpostman wrote: post #8

My experience is that it’s a winner take all field. A small minority of candidates receive huge compensation. They have good degrees and publications. Generally they make 25-50% more than a similar level vanilla software engineer. This is especially the case at top tech companies. If you aren’t one of those, being a regular swe is much better. A lot of ml roles are using canned models, and increasingly so. Many data…

> Generally they make 25-50% more than a similar level vanilla software engineer. It's often even less in my experience. Despite having a "unicorn" skillset (soft-skills, advanced degree, domain experience, and SWE experience), I make about as much as a vanilla SWE. There are a huge number of inexperienced PhDs that want into the field, and we are flooded with resumes every time a DS leaves. Also, most of the time, m…

By ml roles I was referencing research/deep learning type of jobs.

Re: Ask HN: What is the outlook for a new career in ML or DS?

#14

Post by lytefm »

greatpostman wrote: post #13
yold__ wrote: post #10

Earlier quoted context omitted.

> Generally they make 25-50% more than a similar level vanilla software engineer. It's often even less in my experience. Despite having a "unicorn" skillset (soft-skills, advanced degree, domain experience, and SWE experience), I make about as much as a vanilla SWE. There are a huge number of inexperienced PhDs that want into the field, and we are flooded with resumes every time a DS leaves. Also, most of the time, m…

By ml roles I was referencing research/deep learning type of jobs.

Sure "Machine Learning Research at top tier AI company" is a different boat.

I'm talking more about "Data Science/ ML Department at a typical company". You won't see salaries above comparable SWE roles there. Most likely, the SWEs will be better off.

Re: Ask HN: What is the outlook for a new career in ML or DS?

#15

Post by neodypsis »

timy2shoes wrote: post #9
neodypsis wrote: post #5

Are there more opportunities in the MLOps space?

As a hiring manager in the field, my opinion is yes. Companies are realizing reliably obtaining and processing data is harder and more critical than model built. Especially for early stage companies.

Interesting, thanks for the reply. What skills are typically required for MLOps positions?

Re: Ask HN: What is the outlook for a new career in ML or DS?

#17

Post by jstx1 »

Good reasons to move away from DS and ML - not finding it interesting, not enjoying it, having done it for a while and wanting a change. But this

> Now it seems we're on the verge of a centralizing and commoditizing revolution in ML and UX where entire swaths of knowledge producer skills will become obsolete.

this is kind of vague and uncertain, I certainly wouldn't plan my career around it. It's not a good enough reason to change career paths IMO.

Re: Ask HN: What is the outlook for a new career in ML or DS?

#19

Post by rg111 »

moravak1984 wrote: post #3
throwaway298525 wrote: post #2

I'm working in ML, and to be honest, looking to get out. The place I work seems to be rather keen on deskilling, replacing custom models with OTS components, requiring everything be written in Python and so on. I'd rather enjoyed working there the last couple of years, but the fun is slipping away, so I'm planning heading to general web-dev.

Fun is gone, unless you like doing pharaonic "proof of concept" forever. There is still some dumb money out there, but I'm looking to jump ship to web-dev as well (since I'm doing IT anyway just for the money, academia is too corrupt, audiovisual arts are moonshot projects and everything else just sucks).

Yes, true.

There is still dumb money in Proof of Concept kind of work.

And I honestly enjoy doing this kind of stuff.

Re: Ask HN: What is the outlook for a new career in ML or DS?

#20

Post by machinekob »

I don't see anyone writing that ML/DS is a lot harder than a typical SWE and results are a lot less visible for a VERY long period of time.

A lot of the time you could train model prepare pipeline and test enviroment for 3-6 months before you get good enough result to push it into production. And it can get extremely stressful rly fast if you care about that, because not every model is good enough for production so once per year you could have as low as 1 or even 0 models that are working fast and good enough for proper usage and this can burn you after just a 1-2 years of work in the field (I know at least 4 people who just drop ML and go for SWE after 1+ year of ML work and all of them are a lot happier with classical backend/devops jobs).

In SWE after 2-3 days you can have small stuff working fine and after few weeks push your small code into production codebase fixing some stuff or optimising smth as there is a ton of potential in almost every codebase for "easy" upgrades in ML space everything is extremely competitive your results are "state of the art" or they are not if you want to upgrade model it better be sota or you would get asked "why we don't just implement/use ...?".

I still love my job but for sure but I prefer working with ops, classical SWE and deployment then model training, optimising and learning/collecting new datasets (I have 5 years of commercial exp in ML/DL maybe it gets better after 10 years or I'm just boring out who knows)

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