It is a well-known fact in the industry that Google hires the best AI/ML developers in the market. It could be because of various reasons, their brand, products, or employee friendly perks. But one of the significant ones happen to be its strategy.
With the latest spike in the number of businesses using artificial intelligence and machine learning, organizations are struggling to hire AI/ML developers are aren’t only good with their skills, but are keep on continuing to learn.
When it comes to recruitment for a tech job, the focus is given on two things: Skills and Experience. The strategy of hiring an AI/ML developer depends on the skills and the level of experience of the candidate.
However, right from the discussion with the hiring manager, designing machine learning tests, to onboarding, everything has to be crafted perfectly. So, here are a few things that Google does to hire the best in the market:
- The recruitment strategy depends on skillset.
The AI developer skills of a junior level candidate differ not just in proficiency but also in skillset from a senior level executive. A coding test is the best way to determine how skilled the candidate is. During the coding test, you can increase and decrease the difficulty level depending upon the level of experience of a candidate to determine how eligible they are to deal with AI and ML model development.
To find candidates for junior level roles, hackathons, university hiring, and job portals are the best mediums of sourcing candidates. For senior level executives, it is best to find people through networks, academic conferences, referrals, and passive recruitment can help in finding the right talent. - Knowledge of what to look for in a candidate is what helps in making a strategy.
Assess the requirements of your organization and enlist the artificial intelligence skills that you would be focusing on. For most of the machine learning roles, mathematic and statistics abilities, and a strong qualification like a good master's degree or a PhD is what is needed when it comes to designing algorithms to find a solution to a problem.
According to a recent LinkedIn survey in 2020, creativity is a skill that is most desirable in candidates who want career in the field of AI. Curiosity is what drives the innovation, which is what most assessors are looking for in their candidates. To test that, you can throw challenges and questions towards candidates that require a creative solution. - Communication is the key. AI/ML engineers work in a team mostly, which is why their work and their minds need to be aligned. Hence, assessing communication skills of a candidate before hiring is essential. This can be done with tests like English pro test, which is a product of imocha. Not just creativity and communications, cognitive abilities are also something that good AI/ML developers need. Since cognitive abilities deal with the way we process information, learn, listen, and understand, the interviewer should keep such questions handy to ask during the interview.
- Provide the right opportunities to attract the best talent in the industry. While most organizations cannot offer the same remuneration perks as goliaths like Google and Amazon, what they can offer is growth and development. Tell your candidates what’s in store for them if they join, both long and short term. You can even give an example of the projects they’d be working on; this would help in keeping the candidates interested as everyone wants to feel passionate about the work they do.
- Learning opportunities are also a part of growth a candidate will be looking for. Technology is evolving rapidly. So, any AI/ML candidate would want to learn and develop to match the pace of technological development and stay ahead of the competition. Conduct training sessions, offer courses by industry experts to ensure that your employees upskill effectively.
With Digital Transformation, we’re seeing the application of new technologies in our everyday life. Machine learning is the most prominent domain of AI and is widely accepted technology across the globe. Be clear about the job role you want to offer, be it data scientist, ML engineer or data analyst, one of the first point of interaction is the job description. So, it is vital to make it as crisp and enticing as possible.
