Everything you need to know about a career in AI
Worried about the future of work? If you can’t beat the robots, join them.
This week, we’ve been looking at automation, both as a whole and specifically in the world of careers. It probably won’t surprise you to hear that automation pretty much goes hand in hand with the future of work, which, incidentally, isn’t so much in the future any more – it’s in the present. However, to date, the conversations have been around the jobs of the future. And, while many are set to panic about the number of jobs we could lose to automation, there is another side to the story.
We’ve already explored the historical background of the ‘robots taking jobs’ line and, thankfully, we’ve shown that the advances within technology will bring a more skilled workforce and create more jobs as it develops.
Jobs in AI
Jobs in automation and artificial intelligence (AI) already exist, with AI architect considered one of the hottest jobs of the future. But how do you actually upskill and switch into a career in AI and automation? The first thing you need is an understanding of the different levels of expertise within AI.
Neill Gernon is the managing director of Atrovate, an AI lab based across London, Lviv and Dublin. Gernon is also the founder of Dublin AI, a community platform to connect AI engineers and researchers in Dublin. Gernon said within the broad umbrella term of AI, there is a combination of roles at various levels of expertise. “Your foundational stuff is probably your data architects, your software engineers and then your machine and deep learning engineers.”
Beyond those two levels, Gernon said specialist research engineers would come next, including those that specialise in computer vision, language and speech. So, out of the broad range of roles within AI, which ones will be most in demand as we enter the future of work? “All of them,” said Gernon. “A lot of generic software engineers or data engineers are looking at upskilling and jumping on the sexier bandwagon of AI and machine learning by becoming machine-learning engineers,” he said. “They’re all needed for the next generation of AI-powered products. You need specialists that can do the large-scale deep-learning stuff.”