The 6 most in-demand AI jobs, and how to get them

TechRepublic ^ | October 24, 2017 | Olivia Krauth

[2ndDivisionVet]

Robots may be coming for some jobs, but they will likely create new roles as well. Here are some spots humans are needed to fill and how to get them.

It has become common to joke about how robots are going to take our jobs, and rightfully so: Oxford University researchers estimate that 47% of all current US employment is at high risk to become automated over the next decade or so.

But there is positive news: Of the 1.8 million jobs AI will get rid of, the emerging field will create 2.3 million by 2020, according to a recent report from Gartner. And a recent Capgemini report found that 83% of companies using AI say the technology is already adding jobs.

A lot of that growth is coming from the technology itself.

"We'll continue to see job growth in anything AI-related for the next five to 10 years, which is one of the things that will mitigate the oft-publicized inevitable job loss due to AI-led automation," said Brandon Purcell, an analyst at Forrester.

Want to break into a career in the field? Here are the top six most in-demand AI jobs and their average salaries, according to data from job search site Indeed.....

[be-baw]

Interesting article. I see all 6 of the job postings they had were in California.

[Grampa Dave]

Thanks.

I sent this link to some younger relatives still in high school.

[freedumb2003]

"Lube my shiny metal a$$, meat-sack!"

[AnotherUnixGeek]

...and I, for one, welcome our new AI overlords...

[cymbeline]

The six jobs:
1. Machine Learning Engineer (abstract idea been around for 50 years)
2. data scientist (???)
3. Research scientist, deep learning (deep, huh)
4. R&D Engineer, speech processing (that ain’t AI)
5. Business Intelligence Developer (ok they want to call that “intelligence”)
6. Computer vision engineer (that ain’t AI)

Sorry folks, “Artifical Intelligence” is something that isn’t except in article writers’ minds.

[LambSlave]

As someone who has done work in some of these areas, these are jobs that a very select subset of the population could be trained to fill. They require very advanced mathematics skills, programming skills, strong work ethic and independence, creativity, and social skills to either lead/collaborate with the development team. Probably <0.5% of population; I think the article is spot on about the top three jobs at least, but I doubt that the people who lose jobs because of AI are going to be the ones to fill these new jobs, and furthermore the people that do have the potential to fill them will have many other options, to the extent that low six figure income may not be that enticing.

[Wilderness Conservative]

Thank you for saving me the trouble of reading an article I suspected would be a complete waste of time.

[miliantnutcase]

I’m in IT and we’ve installed a lot more automation systems, and self service kiosks at the request of our business. All it does is make more work for us.

[armourenthusiast]

The most important job will be herding the robots back to their “charging” corrals and filling up the autonomous trucks with diesel fuel...kinda like a full service gas station attendant.

[ShadowAce]

$142,000 in SF is not very much

[DoubleNickle]

Just got done reading an another article on this subject...here’s the link:
https://www.nytimes.com/2017/10/22/technology/artificial-intelligence-experts-salaries.html

Cheers!

[Wuli]

The article is merely shilling for the arrogant technologists.

“It has become common to joke about how robots are going to take our jobs, and rightfully so: Oxford University researchers estimate that 47% of all current US employment is at high risk to become automated over the next decade or so.”

U.S. active employment is at about 127 million. 47% of that is 59 million jobs to be eliminated over the next decade.

Then they say:

“Of the 1.8 million jobs AI will get rid of, the emerging field will create 2.3 million by 2020”

That is a difference (if you believe it) of 500,000 jobs, as if they are saying AI will add a net 500,000 jobs. That still leaves a net deficit of 58.5 million over the next decade.

And does any of those “new” jobs apply to the average citizen.

Here are the gaining kinds of jobs and their requirements.

Machine learning engineer - $142,904
Experience required: Software Engineer 5+exp

Data scientist - $141,807
Experience Required:
Ph.D. or M.S. in a quantitative field such as Computer Science, Statistics, or Mathematics -
Minimum 2+ years of professional industry experience in data science -
Expertise in machine learning and statistical modeling

Research scientist - $137,713
Experience required: Background should include three or more years of hands-on experience crafting and experimenting with neural networks, perhaps with additional years applying other machine learning techniques to a particular domain such as computer vision, text, or audio. Research papers or other publicly-visible contributions to the field are a plus. Should be fluent using a neural network framework such as TensorFlow, Caffe, Torch, or Theano and understand in detail how backpropagation works. Must work comfortably in Python and may have experience with common packages such as NumPy, pandas, and PyCUDA. Bonus points for experience with CUDA, the Go language, common database platforms, or search infrastructure.

R&D engineer
Experience required: Ph.D. or ABD (with graduation in 2017) in CS, EE or relevant areas with 0-2 yrs working experience. - Strong desire to integrate research with product development and augment your research abilities with solid programming in C/C and proficiency with SQL, Perl (or Python) and Matlab (or R) - Skilled knowledge of speech recognition, probabilistic systems, statistical models - Strong background in statistical modeling and machine learning - Demonstrate a willingness to learn and apply a wide range of technologies - Experience with linguistic and statistical analysis of natural language would be highly desirable - Experience in designing and running ASR experiments using HTK or KALDI a plus - Strong written and verbal communication skills

Business intelligence developer - $136,486
Experience required: 1+ years experience with AWS Redshift - 1+ year experience with a Data Pipeline product like AWS Data PIpeline (bonus points), Luigi, Airflow, Azkaban - 5+ years experience including development of large scale, complex data architectures - 5+ years experience handling large data sets using SQL - Demonstrated ability to architect and model mission critical BI, OLTP, OLAP, ETL, solutions leveraging multiple DBMS technologies - Experience building data extracts in tableau - Demonstrated ability to architect and model data services - Familiarity with Python - Familiarity with Apache Kafka - Familiarity with S3 and AWS Spectrum - Familiarity with Hadoop or AWS Elastic Map Reduce

Computer vision engineer - $136,152
Experienced required: M.S. or Ph.D. in Computer Science, Electrical Engineering or related field - 2 or more years of related experience in Computer Vision algorithms and Machine Learning techniques - Experience using machine learning toolboxes such as TensorFlow, Caffe, Theano - Excellent skills in Python and tools like Numpy, and Scikit - Expert level knowledge of C, C++ and debugging techniques - Knowledge of data structures and algorithms - Experience working in research oriented environments and reading and interpreting scientific papers.

And how many of these 2+million new AI jobs, with these qualifications, do you think the arrogant technologists are going to fill with H1B visas and merely as hires in their overseas offices? I would say about half.

And those filled as U.S. workers? It will be mostly from present workers in the technology fields whose jobs are themselves being eliminated by technology. So what is the article actually dealing with? It is in reality dealing with merely a shift in the kinds of jobs in the technology industry itself, with most “new” jobs and jobs lost involving people already in the technology field, not “new” jobs for most of the 59 million expected to lose their jobs due to automation over the next decade.

There are all kinds of boasting statements that technology is or is going to create more jobs than it is getting rid of but there is not a single definitive report with any accurate accounting that demonstrates the jobs it is creating and exactly where they are and the numbers. Zip, zilch, nada. This report is merely an inside the technology industry report, and I have serious doubt about the accuracy of its predictions even there. Why? I have read of AI projects that are eliminating technology jobs at every level, which I expect will far exceed this reports predicted 1.8 million.

[bigbob]

AI is defined more broadly than your editorial comments suggest. This is only a partial list by any estimation and its impossible to predict now which will be “top” at some future date.

[cymbeline]

“I’m in IT and we’ve installed a lot more automation systems”

Is automation Artifical Intelligence? Check the Wikipedia article on artificial intelligence. It’s kind of in the eye of the beholder.

[DoubleNickle]

I would think that speech processing and vision engineer could fall under the AI umbrella in the sense that a machine can improve itself by being able to differentiate between dialects of the same language. Basic AI for vision would be like telling the difference between a cat and a dog whereas advancing the program would allow how to distinguish different dog or cat breeds. Layman examples at best but there are AI branches for those two fields.

[central_va]

A person that has all of those qualifications should have a salary of $1,000,000 per year.

[cymbeline]

“AI is defined more broadly than your editorial comments suggest.”

The fact is, I dislike the term “Artificial Intelligence”.

[who_would_fardels_bear]

With regard to "Data Scientist" it seems that a lot more attention is paid to the back-end than the front-end.

By "back-end" I mean the interesting data regression and analysis that happens after all of the collected data has been normalized and organized.

By "front-end" I mean what is sometimes called data "munging", i.e. culling data from multiple sources in a wide-variety of formats and poking, prodding, manipulating, stripping, filling-in, etc. to get it into an organized format.

Maybe we need creative, mathematical geniuses to search for patterns in the data, but isn't it also the case that we need an army of grunt programmers to write a boatload of algorithms to parse all of the incoming data?

Or has someone come up with an AI that can normalize and organize any data from any file?

[LambSlave]

Or has someone come up with an AI that can normalize and organize any data from any file?

I am not aware of any existing hardcore "AI" specific solutions to the data integration problem, but it's being worked and there are many complex applications that facilitate this for specific industries. Also, even in the event of critical need for large scale labor intensive scripting for data integration-- those sorts of grunt programmer jobs are outsourced and wouldn't open up jobs here.