Here are some predictions to exemplify how fast the AI/ML industries are growing:
Because these job roles are skills-based, companies hiring for these roles need to assess candidates based on their knowledge in certain tools and technologies that are required for this line of work. With that being said, here are some of the top skills that your next AI/ML hire must possess.
One of the prerequisites of being a proficient AI or ML professional is possessing technical expertise in programming languages. C++, Python, R, and Java are some of the common programming languages that are needed to create complex algorithms. C++, for instance, is the most basic language that can help speed up the coding process. R, on the other hand, helps in achieving a certain level of efficiency in stats and plots. Java can be used to tackle mappers and reducers. Therefore, it is essential to assess the candidates’ skills in these programming languages in order to hire the best-qualified professionals.
They also need to be well-versed in the fundamentals of computer science. Think of queues, stacks, arrays, trees, graphs, etc., which are a part of data structures. Lastly, they also need to be experts in the basics of computer architecture.
It is always a positive asset when candidates in the software domain have detailed knowledge about probability and statistics. However, when it comes to AI and ML candidates, it is more of a necessary requirement. For instance, they need to possess extensive knowledge about probability and statistics to subsequently understand various AI models and theories. Moreover, statistics help programmers become efficient AI professionals, and they also use statistics to evaluate data and models.
AI and ML professionals’ deal with overwhelmingly large data sets on an average workday. This is where having knowledge of distributed computing can be a very useful tool for them. It is important to evaluate candidates' distributed computing skills because employees who are skilled in this area will greatly contribute to your firm's success through their ability to efficiently analyze data.
Feature extraction is one of the mainstays of both ML and AI. Hence, the professionals must be knowledgeable about advanced signal processing techniques. These techniques include, but are not limited to: curvelets, shearlets, bandlets, wavelets, contourlets, and so on. Along with this knowledge, they should also be proficient in time-frequency analysis and know how to implement it in a multitude of scenarios.
The ideal candidate in the AI domain needs to be an expert in algorithms and applied mathematics. They should possess exceptional problem-solving skills and analytical skills. These are two of the necessary foundations of finding optimized solutions for common problems. Equipped with this knowledge, they can effortlessly complete the complex tasks they will typically face.
Bonus Tip: Do your potential AI/ML hires regularly participate in tech gigs and hackathons? Are they interested in exploring more about their niche? How much interest do they take in learning about the latest AI/ML trends? Affirmative answers to these questions mean that you have found the best candidates!
There is no shortage of candidates who want to take the leap to become successful AI/ML professionals. They all come from various backgrounds and often possess many different skill-sets. When you are hiring such professionals in bulk, it is immensely important to assess each individual's strengths and weaknesses.
We're all aware of the difficulties we face in choosing the best candidates for technical job roles. So, to avoid the risk of a bad hire and reduce the time-to-hire, make a pre-employment skill assessment solution a part of your recruitment process.
About the Author: Pankaj Deshmukh is in the field of digital marketing. He works with Interview Mocha and produces content for the variety of blogs that cover topics from recruitment, social media hiring & candidate assessment. He believes that learning is never ending process and stays updated with the latest trends that are useful for producing valuable content.