AI engineers: Your secret sauce toward making millions of dollars.
Haven’t you heard? Amid the pandemic attack, technology workers having artificial intelligence skills were spared from layoffs.
Employment opportunities are only bound to increase as sectors such as schools, healthcare providers, and businesses look forward to developing smarter applications and advanced analytics to fight the attack.
A report by IDC says the hiring spree for AI jobs could increase to 16 percent globally by the end of 2020. As such it may hit 969,000, an estimated number was driven by the strong demand for AI skilled professionals.
With AI as a guide to make informed decisions, these expert professionals are already hitting the job market and revamping their AI skills through AI certification programs.
From automatically getting suggestions for the next trip online to predictive texts on google search, AI is already upon us. The limitations of what AI can do doesn’t stop here, the technology is also capable of making a spell check for us, improve grammar, help doctors diagnose diseases, and even predict weather conditions.
Before taking a leap to know about the roles and responsibilities, let us first understand the simple annotation of AI. Artificial intelligence or AI is a process of making machines intelligent. Simply put, it is an engineering mechanism that allows the computer system to learn and behave like humans. If an AI professional teach a computer to behave like a human, it would – simple dynamics of how to make a machine learn.
As an AI engineer, your major agenda is to make computers understand how human work and function accordingly.
Roles and responsibilities
An AI engineer builds, maintains, and deploys AI-based systems. Their core responsibility is to make sure the AI systems and infrastructure are properly deployed within the organization.
Their roles and responsibilities can also differ from industry to industry. However, AI engineers can have multiple responsibilities which include: -
• Creating and deploying AI-based systems (as mentioned above)
The AI-based system generally runs on algorithms. Now, these intelligent systems with the help of iterative processing enable the software to learn things on its own. The AI professional helps in developing these codes required by the machine to function. The individual needs to first study the product’s requirements based on which the codes are developed later.
• Designing software
Extensive knowledge in machine learning, model building, and validation. These highly skilled professionals are responsible for deciding which model needs to be kept ready for deployment and whether it needs to be further retained or not. The major agenda of AI is merely not only about creating machines but to create machines capable of self-analysis.
• Analyzing data
The job of an engineer is to collect the data and further run it against the machine learning algorithms. Doing so allows them to identify various possible pitfalls to come. Besides this, they help in collaborating with business analysts, architects, and data scientists just to make sure the analytics is aligned to the company’s business goals. They need to keep themselves updated with the latest happenings around the world if they need a breakthrough in the AI field.
For any engineers working on large-scale projects, working with big data is a must. Data analysis is majorly used to identify the right solution for complex problems.
• Image processing
It makes machines and robots easily analyze and react to what they see with the help of image processing algorithms. From the perspective of an AI engineer, this simply means that the machine can identify problems and other related problems in the production process or any manufacturing process. AI has and will continue to be an integral part of the engineering field.
• Natural language processing (NLP)
Natural language processing is the field of study that helps improve the capability of humans and machines to communicate. Their major goal is to ensure how machines can respond to a human command. NLP uses big data and algorithms that help them work efficiently. The most common examples include Siri and Alexa.
Will a career in AI make you a millionaire?
Nothing can stop the technology from progressing. AI professionals with limited AI skills or are void of industry experience are already making somewhere between USD 300,000 and USD 500,000 per annum in certain parts around the globe.
You can imagine the kind of packages a highly-skilled professional would make.
There’s no hiding here, top organizations are paying AI engineers more than any other techies out there. Demand for AI professionals is growing at breakneck speed as compared to the supply in the AI talent pool. In addition to the signing bonuses, companies are willing to compensate the AI workers with sky-high salary packages.
The highest pay scale of an AI professional is in China. A senior research scientist in China makes around USD 567 – USD 624 thousand per year. While other AI experts and ML experts around the world are making USD 315 – USD 410 thousand per year.
Currently, China has approximately 300,000 skilled AI experts and AI engineers. But this number does not suffice the current requirement.
Organizations need million more AI experts to fill the lacunae.