Skilled AI engineers are a difficult-find for almost any top company, across business domains. The reason – lack of industry-specific AI skills among candidates appearing in the interviews. Hiring remotely-working AI specialists has become a trend off late in the global business landscape, given the need for Artificial Intelligence (AI) engineers for industry-specific projects that last until a specific period of time. That’s a clear indication to the AI industry aspirants to develop skills keeping in mind a target industry, or business sector. It’s project-based hiring for AI & ML (machine learning) engineers that is in trend instead of recruitment for full-time job roles.
Global automation market size by segment, amid 2019 & 2021
The global pandemic led by Coronavirus spread has further fuelled the hiring of remote AI engineers. As per the Global Leadership Summit held in London, 34% of employers on being asked about their staff working remotely, said that more than 50% of their full-time workforce will be performing their job duties remotely, in 2020.
Tech Giants are Hiring Remote AI Specialists as Added Resources
A lot of tech companies these days are hiring remote AI specialists and engineers from a variety of geographical regions, as they are looking for the best among the best. These remotely-working AI experts are being hired in addition to the current team of AI professionals at the organization. Most of such experts possess a specific set of AI skills that are relevant to a particular industry. If you as an aspirant would like to get employed as a remotely-working AI expert who possesses specialization in a specific industry, enrolling into industry-focused ‘AI engineer certifications’ will help immensely.
3 Steps to Hiring a Right AI Candidate
AI job roles with highest salaries in the U.S. (2019)
Determining the Specific Business Needs
In the role of a hiring manager at a tech firm, before you hire an AI professional, you must check for the business-specific needs. These would comprise identifying the amount of training data you possess, how refined is your data, how much cleansing would be required to be done by the new hire to make the data usable for creating an ML (machine learning) model.
Having a decent data infrastructure is much-needed before you actually hire an AI specialist to work with business-relevant data. Having a large pool of relevant data ready to work with, is a fundamental requirement to hiring an AI expert, as it’s the data that will allow this new person to develop a new AI model specific to the business needs.
Finding the Perfect Talent
Searching and shortlisting the right talent is crucial to the business growth in long term. According to the findings of an Atlas research, a ‘work-from-home life’ is the second most preferred choice among the technology candidates in the context of job benefits. The said research found programmers and software engineers listing remote work as their second preference, with 53% of the surveyees agreeing to it. The most preferred work benefit was found to be ‘vacations and leaves’ with 57% of respondents in its favour.
Identifying the Right Candidate
As a business looking for an AI expert, your aim should be to finding someone who possesses soft skills, is a great communicator, and thoroughly understands both, business and technology requirements. These professionals will not only prove to be great AI engineers but would also serve as great leaders who can handle a team of tech professionals as well as communicate with those folks who don’t understand complex technology.
Finding such perfect AI talent would require the engineering and business stakeholders at the organization to interview candidates and ask relevant business-specific & technical questions (statistical and mathematical), and basis the answers, decide whether the candidate is a perfect fit.
A skilled AI engineer holds the ability to communicate about what they have done and what they are planning to do when conversing with the non-technical people in the higher management, or when speaking with the stakeholders who are not tech-savvy. And herein, the soft skills come into play.