[HN Gopher] Ask HN: What is the outlook for a new career in ML o...
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Ask HN: What is the outlook for a new career in ML or DS?
More specifically, I'm in my early 30s and have been disabled with
post concussive syndrome and ME/CFS. I've been slowly hacking away
at a math, coding and ML knowledgebase in concert with efforts to
increase my work endurance, with the intention of accruing hard,
demonstrable skills that could serve me well in any capacity. I
assumed this was the most robust use of my limited energy because
these skills could be used in almost any white collar position
which uses computers to perform repetitive tasks or intersects with
structured and unstructured data. At least, that was the idea x
years ago. 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. Where will that
leave people trying for either ML engineer or more data analysis
focused DS roles? Or even just everyday utility
scripting/automating powers? Can even the latter two can be largely
replaced by hybrid finetuned multi modal language/code models. I
feel a bit lost and like I have wasted my time. Will only elite
scientists in the top percentiles of skill and resources be needed
or will the future have room for more pedestrian aspirants?
Author : MLwannabe
Score : 14 points
Date : 2022-11-27 19:51 UTC (3 hours ago)
| aborsy wrote:
| The universities produced so many data science and ML graduates
| in the past decade that got me really worried. Swaths of people
| from all branches of engineering relabeled themselves as Data
| Scientists.
| cloudsec9 wrote:
| 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.
| throwaway298525 wrote:
| 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.
| moravak1984 wrote:
| 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).
| bmitc wrote:
| > requiring everything be written in Python
|
| This is the number one thing that doesn't make me want to even
| try the switch. I am trying to learn some machine learning for
| educational purposes, but I have free choice to use what I
| want: F#, Python, and Racket.
| nnoitra wrote:
| breezy12 wrote:
| I'm an engineer, late 20s, who recently received a pcs diagnosis
| and went on short term disability so far. Just wanted to say it's
| awesome you're being proactive. It's a rough time. Hope you feel
| better soon.
| greatpostman wrote:
| 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 science insights are ignored by the business, or the
| statistics don't work on such a biased sample.
| yold__ wrote:
| > 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, models don't really
| matter. What makes or breaks most DS projects is soft-skills,
| stakeholder management, and data cleaning / feature
| engineering.
| lytefm wrote:
| > 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.
| greatpostman wrote:
| By ml roles I was referencing research/deep learning type of
| jobs.
| lytefm wrote:
| 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.
| neodypsis wrote:
| Are there more opportunities in the MLOps space?
| timy2shoes wrote:
| 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.
| neodypsis wrote:
| Interesting, thanks for the reply. What skills are typically
| required for MLOps positions?
| jstx1 wrote:
| 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.
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