
Ask HN: How many machine learning or other research-type jobs are there? - epicureanideal
As patio11 says[1], 90% of all software is line of business software.<p>Where are the other 10% of jobs?  How are they distributed?  One or two people per company?  (I worked for a company with 2 research-type engineers out of 10ish total.)  How large is the team inside Google or Amazon?  What are the qualifications needed to get into those positions?  Are they significantly better paying?  Are there more skilled people for these positions (like in academia), or more positions than skilled people?<p>Basically, it seems that there is some missing information about the market, and I&#x27;m not sure how much effort to put into training for a highly specific skill set without specific information about the potential benefits.<p>[1] http:&#x2F;&#x2F;www.kalzumeus.com&#x2F;2011&#x2F;10&#x2F;28&#x2F;dont-call-yourself-a-programmer&#x2F;
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tgflynn
Several years ago I worked for a very large company in a rather small group
(about 40 people) that worked on what were then challenging image recognition
problems. I think that most work in these areas is done either in large
companies like Google, Microsoft, IBM, etc. or in a few small startups that
are founded specifically to tackle these types of problems by people with very
strong backgrounds in them (often from academia).

 _What are the qualifications needed to get into those positions?_

In my opinion the ideal background would probably be an undergraduate CS major
with a minor or a lot of course work in applied mathematics (at least at the
level required for an EE or physics type degree) who has developed very strong
practical programming skills. This would ideally be followed by a masters or
PhD in machine learning. Many people get into the field without these kinds of
qualifications through self-study, however (unless they're looking for a job
in academia or a place that is specifically considered a "research lab"). The
minimal requirements to learn the field are probably being comfortable with
applied math through linear algebra and vector calculus with at least some
statistics and probability along with strong practical programming skills.

Aside from all this the _sine qua non_ of getting a job seems to be getting
good at handling technical interviews.

 _Are they significantly better paying?_

I doubt it. That's mostly a question of supply vs. demand (see next question).

 _Are there more skilled people for these positions (like in academia), or
more positions than skilled people?_

This is a complicated question. On the one hand the field seems to be
exploding now and there are potential applications in practically all areas of
human activity. There certainly aren't enough qualified people in the world
right now to even scratch the surface of what can be done.

But that doesn't necessarily equate to there being a lot of jobs. I don't know
what the job market is currently like but in 2011 it certainly wasn't easy for
an experienced person to get a job in this field (it might have been easier
for a young person with strong academic qualifications, however).

The problem is that developing a machine learning application to the point of
generating revenue is typically very difficult and can take years. From the
point of view of most investors it makes more sense to put money into
developing a mobile app or a SaaS or something technically much simpler. Also
even if you do want to found a machine learning company finding enough skilled
people is probably not easy.

