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.

SEE: IT leader’s guide to the future of artificial intelligence (Tech Pro Research)

1. Machine learning engineer – $142,904

Example job posting: Machine learning engineer, recommendations for Pinterest

2. Data scientist – $141,807

Example job posting: Data scientist for Indeed

3. Research scientist – $137,713

Example job posting: Senior research scientist, deep learning for Clarifai

4. R&D engineer

Example job posting: Research Scientist R&D Engineer – Speech Processing/Recognition for Pearson

5. Business intelligence developer – $136,486

Example job posting: Business intelligence engineer for EVERFI

6. Computer vision engineer – $136,152

Example job posting: Computer vision research engineer for Gracenote

As the field grows, most experts agree that few, if any, current AI jobs are going to fall out of style and stop hiring.

“I always joke that the safest job on the planet is AI researcher,” said Toby Walsh, an artificial intelligence professor at the University of New South Wales. “When we’ve automated AI researchers, the machines will literally be able to do everything else by definition.”

Most of these in-demand jobs require similar skills, including strength in mathematics and machine learning skills.

“There are certain technical requirements that tend to be pretty standard, such as a CS degree or programming skills,” said Raj Mukherjee, senior vice president of product at Indeed. “Though from Indeed’s data we are also seeing that a background in programming languages such as Python, Java, C/C++, and past experience in artificial intelligence, machine learning or natural language processing are all top skills employers look for in applicants.”

How to get a job in AI

Outside of having the standard skillset and education, there are other ways to be a strong candidate for these lucrative gigs. Here are five things experts recommend to improve your application, whether you’re working in the field already or not.

1. Check out online courses. Like many tech-based fields, there are several online courses for AI topics, allowing someone to learn more about the field as a whole or gain more specialized knowledge. Some options offer certifications that can bolster a resume, Purcell said.

2. Join outside organizations. Learning from others in the field can help improve your skills, so check out local hackathons or similar meetups. Getting involved with organizations like DataKind allow data scientists to work on new data, practicing and growing their skills while learning from their peers, Purcell said.

3. Add standard business knowledge. Many of the in-demand AI jobs are technical by nature, but knowing how to translate those developments to other businesses or consumers is important for any organization, Purcell said.

“Since these folks are typically very technical, they don’t necessarily have the business acumen necessary to translate the results of these models into operationalized AI systems that impact the bottom line while having a positive impact on the customer experience as well,” Purcell said. “So there’s also increasing demand for a different skill set that includes familiarity with AI techniques as well as deep business and domain expertise.”

4. Read–a lot. Multiple experts agreed: Those working in AI should always be learning, and reading is a way to do that. Roman Yampolskiy, director of the Cybersecurity Laboratory at the University of Louisville, recommended subscribing to scientific publications.

“The real trick is to read. Read a lot. Not just your own area but all the related areas. And a few things even more distant,” Walsh said, recommending science and nature topics across multiple platforms.

5. Be a sponge. AI is a rapidly developing field, so Mukherjee recommends being prepared to explore as many experiences and opportunities in AI as possible.

“Keep up to date on latest research in AI – there is so much advancement happening every single day,” Mukherjee said. “This may include looking for opportunities inside their current workplace or outside. Make sure that they do not get pigeon holed into one area.”

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