The growing reliance on workplace robots in business today has sparked demand for ‘robot creators,’ IT professionals with niche skills and qualifications, according to recruitment firm Hays.
There are five key roles that are required in the age of robots, the firm said, including robot programmers, robotics engineers, senior engineers, machine learning engineers, and various technicians.
“It’s important to realise that while automation is here to stay, it won’t happen overnight,” Hays CIO Steve Weston said. “Even so, we mustn’t rest on our laurels. These new technologies will demand different skills from our IT teams and create new jobs.”
Weston said organisations need to prepare by ensuring their IT infrastructure is fit for purpose and they have the necessary skills at their disposal.
He said roles and sectors which have traditionally not featured any automation are now seeing robotics become part of the process, ranging from fruit picking to health care.
One area where Hays expects to see many big changes over the next decade is the automotive industry, as self-driving cars are introduced and new technology is incorporated into vehicles.
According to Hays, workplace robots are having a big impact on IT infrastructure and departments and will require the support of niche IT experts.
Hays outlined the skills required in each of the five key roles, explaining it is the role of the robot programmer to create tailored code to enable the machine to execute its tasks efficiently and effectively.
“As well as a relevant degree and extensive training, robot programmers require people skills to liaise with clients so they can customise each machine to perform its desired function,” Hays explained.
Robotics engineers, meanwhile, combine skills from a range of engineering disciplines in order to design, build and maintain complex robotic machines. “They are typically qualified to degree level in either electrical, manufacturing, industrial, electronic or mechanical engineering,” Hays explained.
Senior engineers are educated to at least degree level, and those at the cutting edge are likely to have specialist postgraduate qualifications in cybernetics and systems science research, while machine learning engineers focus on enabling computer technology to acquire intelligence in addition to that contained within its programming.
“Requiring skills beyond traditional computer science and programming, machine learning engineers need a solid understanding of probability and statistics as well as data modelling and evaluation.”
Hays also noted a multitude of technicians are needed, which would provide support and specialist expertise typically gained through hands-on apprenticeship schemes and classroom instruction.
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