Career Opportunities in Signal Processing and Machine Learning

[euoi]

Hi all,
I'm considering doing a masters in either signal processing or machine learning. I have a bachelor's in electrical and electronic engineering, and have a bit of experience (internships mostly) in both industry and research. I was wondering if there are a lot of career opportunities when it comes to either of these two fields?

From my limited experience, I have found that I really dislike paper-pushing and administrative/managerial jobs.. I'd really prefer something technical where I actually utilize what I've learnt. I was thinking of going into image or audio processing, where there's some overlap between machine learning and signal processing. However, I've been hard-pressed to find people in this field. Are the jobs rare?

Also, I have heard from some that machine learning jobs are mostly in academia. Are there any openings for machine learners in industry?

Would really appreciate any input you have. Thanks in advance!

 

[story645]

I was thinking of going into image or audio processing, where there's some overlap between machine learning and signal processing. However, I've been hard-pressed to find people in this field. Are the jobs rare?
Also, I have heard from some that machine learning jobs are mostly in academia. Are there any openings for machine learners in industry?

Check ACM and IEEE and then extrapolate from what they offer to figure out which industries you should be looking at. Try the careers sections of any major audio company (Bose, Dolby, etc), camera company (Panasonic, Sony, etc.), and computer card company (Nividia, Soundblaster, etc.) I don't know where you're at; location could be playing a factor in the lack of jobs you're seeing.

http://jobs.acm.org/c/search_results.cfm?site_id=1603&max=25&keywords=signal+processing&search=Search but a few of them look like jobs where there would be other positions at the company for people with the same skills.

Experience in AI and machine learning is considered a plus for the financial industry, but I don't think much of it is applied. You may also want to look at search engines, data mining companies, and pretty much anyone else how you think may deal with large swarms of data they want to make sense of.

 

[neergmas]

I have looked at countless job postings and PhD programs related to DSP and computational statistics.

Like story645 said, machine learning (AI, data mining, computational statistics) will get you into the financial area (get ready to live in NYC and be "treated like a slave"), although you will also probably need to come from an ivy league school for those jobs and a lot of time they want a PhD in something technical or an MS in Financial Engineering. Hard core data mining/statistics are used a lot at biopharmaceutical companies -- you'll need a PhD for those jobs though. Also, like you said, academia will gladly take you. Oh, and if you can get a clearance (assuming you're US), the DOD likes to mine for data. Mostly PhD jobs!

Going the DSP route will definitely offer more MS opportunities, and, as computing power increases, we will find it more feasible to implement complex computational statistics algorithms in firmware. Although there will always be a need to be able to implement efficient DSP on tiny devices, because Moore's law will eventually put a processor in even the most worthless piece of trash.

As an aside, here is an image I created last summer from scraping the returns for the search "DSP" from a popular job site:

http://www.neergmas.com/files/images/jobMap/DSP.png

You can kind of see where you're probably going to live. My code is gone now :( or I would make another for "machine+learning". Spend some more time on Monster. Good luck!

 

[euoi]

@story645
Thanks a lot! Was unaware that IEEE and ACM even had career pages. A lot of embedded software stuff.

@neergmas
Thanks for your input. Hmm, seems that if I want to do machine learning, I should go all the way and get a PhD.
Cool visual :-)

Seems like I have a lot of thinking to do. Thanks all. Really appreciate it.