The Must-Have Roles of AI Engineers in 2020

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The future of artificial intelligence (AI) should fill us with optimism rather than fear.

The new-age technology is poised to impact the future of virtually everything we see. Be it the industry or human beings, the change is already happening. AI today is the key factor that drives other technologies like the Internet of Things (IoT), big data, and robotics, etc. thus, it will continue to be the key driver for business growth.

As we enter the new era of 2020, AI engineers and AI engineering will greatly influence the current economy. The AI industry is seen to proliferate in the jobs market as businesses look forward to improving competitiveness and gain relevancy in the current economy.

Based on research, 2020’s jobs list, it is said to entail almost 50% job openings in the field of engineering and development followed by robotics which appeared for the first time.

AI affecting the engineering sector:

AI has caused quite a significant impact in the engineering sector. For instance, the AI used in engineering combines both software and hardware components as such that it makes the machine smarter and highly efficient.

Machines are now much more intelligent, in fact, they’re capable of learning and improving processes even without human intervention.

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AI engineers: Major key roles

The roles and responsibilities of an AI engineer solely depend on the kind of industry.

However, the majority of AI engineers’ core responsibility is problem-solving along with making sure the AI systems and infrastructure are in proper alignment in the organization.

Their primary role also entails working with machine learning. As an AI engineer, the expert needs to devise AI solutions and apply the right solution to a problem.

The job role of these engineers has been claimed to be one of the top spots in most of the job portals. They understand business problems, setup and manage AI deployment and production infrastructure. AI product managers along with stakeholders gain significant benefits from these engineers as they help them understand the potential and limitations of AI while planning to build a new product.

Here are some of the job roles: -

👉1) Develop and build an infrastructure for data science

Since AI is widely used during data extraction and analysis, the job role of an AI engineer over here is to make sure the environment that is created during the development process should be replicated and managed easily after getting the final product.

Besides this, they need to ensure the setup and managing production and development of AI infrastructure is taken care of.

👉2) Software designing

The majority of AI engineers are expected to have extensive knowledge in machine learning, validation, and model building. The final decision making is made by them to ensure whether the model is ready for deployment. If it isn’t, it is their call to check whether it needs to be replaced or retained. Their main goal is to teach the machines how to learn and most importantly teach these machines self-analysis.

👉3) Natural language processing (NLP)

NLP is a study that involves improving how humans and machines communicate. The major aim is to improve the way the machines respond to the voice command. NLP makes use of big data and algorithms to help them function better.

Some of the great examples that already exist include names like Siri and Alexa.

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Image Source: neovasolutions

he goal is to make these machines understand human voice up to an extent where the machine will be able to deduce what the individual wants and then present it with a newer set of commands.

👉4) Creation and deployment of AI algorithms

Now the AI-based systems only run on AI algorithms. In combination with iterative processing, the intelligent AI systems offer the software the ability to learn on its own. The toughest task for these engineers is coding — they write codes that apply to an AI machine to function.

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Image Source: KD Nuggets

Developing an AI-based system is not an easy task. The engineer needs to study the requirement of the product, then understand the kind of logic that needs to be used before writing the code.

👉5) Image processing

With the help of image processing algorithms, it gets easier for machines and robots to identify what they see and then accordingly react. From the eye of the engineer, this simply means that the machine can identify the structural problems taking place during the manufacturing process. AI is significant in the engineering field and will remain to be so as engineers will be the key drivers of innovation not just for the IT industry but for the other industries as well.

👉6) Data analysis

AI engineers gather the data then run it against machine algorithms to ensure they first identify the drawbacks. This is a collective work of an AI engineer, AI architect, and business analysts — they ensure that the analytics on the back-end is well aligned with the business objectives of the organization.

As an AI engineer, they’re expected to stay updated with the recent trends and breakthroughs happening in the AI industry. Also, for engineers working in larger industries or large-scale projects, working with big data is the normal trend.

AI has undoubtedly made its way into the industries. For organizations to stay up to date, they will require to hire engineers from the AI field. But with a shortage of AI talents, their only escape is to search for AI professionals’ adept in AI skills.

As AI predicts to increase labor productivity by 40% and above by 2035; it is evident that the demand for AI engineers will skyrocket. Therefore, the need for AI professionals will rise exponentially, thus, creating value for those looking to pursue their career in AI. As a matter of fact, candidates can now opt for AI engineer certification programs to gain a competitive edge in the AI world.

It is time to accelerate your AI career as the AI future may come faster than you think!

Written by

AI Researcher, Writer, Tech Geek. Working on Deep Learning & Neural Networks. #cobots #coding #algorithms

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