Roles Technical Areas AI Engineers

Roles and Technical Areas for AI Engineers


Roles and Technical Areas for AI Engineers. The field of artificial intelligence (AI) is a relatively new field with newfound career paths. For every AI expert looking to start a career in tech, there are several promising technical areas to land a career.

As recruiters, you should also learn how to spot promising talent, even without enough working experience. Design your company’s recruitment strategy to prioritize talent and creativity over the number of years on the job. Hire AI developers with a massive array of talents.

For job seekers, you can cast a wider net by looking for generic roles. As you gain more experience in the business, you can focus on specific career directions and tailor your interests to particular fields. Roles and Technical Areas for AI Engineers. 

With that in mind, let’s look at some promising career choices for AI technicians in 2021. It all depends on your interests and qualifications.


A degree as an AI engineer places you in an excellent position to become an educator in this sphere. You can also publish papers and detailed research on AI-related topics. At the same time, an AI technician can organize seminars and workshops to lecture people on the latest implementations and advancements in artificial intelligence. They could also focus on more niche-specific applications of AI like Business Intelligence (BI).

Mathematics and Statistics 

Mathematics is a close relative of artificial intelligence. And since most engineers will be working with data and statistics, they need to show a high proficiency in maths. At the same, this proficiency gives them an advantage when working on complex mathematical and statistical models for automated projects. Besides, an AI engineer should know how to evaluate a real-world problem and provide a math-based solution. This skill can also come in handy in academia.

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AI development 

Your job as an AI developer involves creating software for AI robots and systems. As an architect, you need to build AI-integrated services for clients. 

To become a well-versed AI engineer, you need to acquire skills in programming languages like Python and C++. At the same time, you should also dedicate more focus to the AI-related aspects of each programming language. 

Since your work requires constant interaction with massive amounts of databases, focus on Apache Spark, MongoDB, and other big data technologies.

Machine learning

As a machine learning engineer, your responsibilities revolve around creating predictive models based on large amounts of obtained data. As a result, you need to hone your machine learning skills. Get acquainted with the latest deep learning frameworks and algorithms.

Data Science

AI engineers often end up as data scientists because of their experience working with data. But to distinguish yourself as a data scientist, you need to show expertise in data collection, analysis, arrangement, and interpretation.

What should recruiters consider when hiring AI developers?

Instead of focusing on the years of experience on the AI developer’s resume, pay more attention to their real-life solutions to problems. These projects offer useful information on their problem-solving abilities.

Most importantly, focus your recruitment policy on the company’s needs. Don’t hire AI developers that don’t fit within the company’s mold. If you need a data scientist, hire an engineer with experience in working with large amounts of data.

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