Tips for Breaking into the UK’s Thriving A.I. Marketplace

If you’ve considered a career in artificial intelligence (A.I.) and machine learning, your employment prospects look brighter with each passing day.

It seems like there’s a new A.I. company launching almost every week, and with the government planning to supercharge the industry, the demand for talent is bound to keep rising.

“We’re all hiring,” said Marcus Neale, recruiting partner for Jazz Networks, a startup provider of network and data security driven by A.I. and machine learning. Best of all, many early stage companies are willing to consider passionate newcomers who meet some basic criteria. But interested tech pros also need a plan to pinpoint and pursue specific interests.

With all that in mind, here’s a look at the hot opportunities in the space, as well as some ways to make yourself more marketable.

Finding Your Niche

Tech pros who want to get involved with A.I. can choose a career path that fits their timeline and risk tolerance.

If you fall into this camp, you can pursue a position with one of the early adopters, or the roughly 34 percent of global companies that are currently using some form of A.I. in their IT departments. According to the Gartner hype cycle, we are about two to five years away from mainstream adoption, with 42 percent of companies planning to ramp up spending over the next five years.

As it stands, opportunities to integrate A.I. and machine learning into traditional tasks involving network security, programming or software deployment largely exist in the technology, telecom and financial services industries.

Ultimately, if you want to spend most of your time working on advanced projects involving voice recognition, robotics or natural language processing, you should consider joining a startup. To find your niche in the diverse startup ecosystem, start by identifying the types of problems you’d like to solve using A.I., advised Richard Downes, a specialist in data science, A.I. and machine learning recruitment with Stirling Global.

“Dedicated A.I. companies put more emphasis on problem solving and less emphasis on a specific tech stack when they look for new hires,” he explained. It’s not enough to be interested “just” in working with A.I. he added; to succeed, you need to be equally interested in helping the company achieve its mission.

Most of the A.I. startups in the UK encompass healthcare, automotive/autonomous driving, computer and data security, financial services, insurance, customer service, marketing/advertising and the Internet of Things (IoT).

However, with 121 companies to choose from, there is something for everyone. For example, some startups are using the power of A.I to streamline knowledge work such as software development, recruiting, research, or data analysis; others are working on preventing disease and food shortages. To help you find your passion, here’s a partial list of the A.I. startups that have raised funding in 2017.

Boosting Your Appeal

Generally speaking, you need a degree in science, preferably computer science or engineering, physics or math, and hands-on experience—which can be acquired through open source projects—to compete for a position. Once you acquire some practical experience, you can reassess your interests and decide if it makes sense to pursue an even more advanced degree.

“Experience and the ability to learn on-the-job trumps academics,” according to Neale, so be sure to list self-taught skills and relevant side projects at the top of your CV.

For instance, Jazz Networks recently hired an aeronautical engineer who demonstrated a passion for machine learning and its associated architecture requirements by participating in Kaggle Competitions.

While it helps to know Python or Java, recruiters insist that experience with any programming platform will do. Downes advises those interested in A.I. to attend meet-ups and conferences, stay up on events, and network with the industry’s thought leaders.

While taking free online courses in A.I. and machine learning fundamentals is a great way to acquire baseline knowledge and demonstrate passion, prospective employers want to see how you’ve applied your skills and what you’ve learned. For most positions, experience trumps education.

Developing A.I. requires an innate sense of curiosity, logical thinking, and the ability to analyze massive data sets and craft algorithms. “Highlighting the problems you’ve solved and the tools you’ve used in your CV and during interviews is the best way to make yourself more attractive to prospective employers,” Downes advised.

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