Essential elements to know to be an Artificial Intelligence Engineer

Essential elements to know to be an Artificial Intelligence Engineer

AI market will grow to a $190 billion industry by 2025.


The rapidly developing area of technology is full of exciting and innovative career opportunities. Artificial Intelligence (AI) is an immensely growing industry, which offers several new challenges and endless opportunities for professional development. Artificial Intelligence is among the largest technological wave, which has hit the world of tech. The global AI market will grow at a rate of 154 percent. This resulted in the high demand for AI engineers in the recent times.

In this article, one can get a clear idea of becoming an artificial intelligence engineer.

Who is an Artificial Intelligence Engineer?

Professionals who possess sound knowledge in artificial intelligence engineering work on AI technology. They create, test, and implement AI models, along with the handling of algorithms, neural networks of the AI infrastructure. They also leverage the traditional software models and various other Machine Learning (ML) models. With the development of AI and ML in different areas of the IT industry, the demand for these AI professionals is very high.

What are the roles and responsibilities of an AI Engineer?

Based upon their experience, knowledge of the domain they work for AI engineers are required to perform certain tasks in general. Those responsibilities include:

  • Study and transform data science prototypes
  • Develop the machine learning applications into application program interfaces (APIs) according to requirements so that other applications can use them.
  • Build AI models from scratch and help the product managers and stakeholders of the company. Explain to them the results they can attain from the model.
  • Research and implement appropriate ML algorithms and AI tools
  • Build data ingestion and data transformation infrastructure
  • Set up and manage AI development and product infrastructure
  • Stay updated with the latest developments in the field
  • Be a good team player, it is very essential to coordinate with others.

There are various ways one could be an artificial intelligence engineer. So, let’s understand how one can be in this growing profession.

Academic prerequisites to be in the field of artificial intelligence engineering

Let’s understand the prerequisites that are required to be a part of this growing industry.

  • One must have a bachelor’s degree first in computer science, mathematics, information technology, statistics, finance, or economics.
  • Having a master’s degree in computer science, mathematics, cognitive science, data science, or artificial intelligence will be a great added benefit too.

Building technical competencies

To an AI engineer, the next step after completing a bachelor’s degree in one of the above-mentioned streams is building technical competencies that include:

· Programming Languages

There are many programming languages for artificial intelligence, to keep up with the latest advancements, it is important to learn programming languages. The most prominent programming languages for artificial intelligence are as follows:

  • Python
  • R
  • Java
  • C++

· Deep Learning and Neural Networks

Neural systems are designed according to the human cerebrum that can perceive numerical examples dependent on tactile information. The world of AI has advanced from single-layer neural systems to deep learning neural systems. In these systems, information is gone through several layers for increasingly complex example acknowledgment.

· Natural Language Processing (NLP)

Natural Language Processing (NLP) consolidates two of the significant regions of ML and AI: linguistics and computer science. The chance of AI engineers working with either content or sound or video is high. Along these it is crucial to have knowledge of the following libraries:

  • NTLK
  • Gensim
  • word2vec
  • Sentiment Analytics
  • CoreNLP

One can build their technical competencies by doing an artificial intelligence certification that offers a better understanding of the co       re concepts

Essential business skills

To develop a career in the field of AI, an individual should possess some soft skills in addition to the technical competencies that are mentioned above. The soft skills include:

· Problem-solving

In the field of AI, it is important to solve complex issues faced by humans. An individual must have good problem-solving skills to tackle the issues effectively.

· Analytical skills

Artificial Intelligence engineers are required to review and interpret critical data. To do this effectively, they should analyze information, build insights and brainstorm possible solutions.

·  Business acumen

Successful AI projects can solve the firm’s major issues. Possessing business acumen gives an individual to convert technical ideas into effective business projects.

Pursue relevant AI certification

The AI certification will help an individual to get an appealing salary in a well-established organization. The average salary per annum of an artificial intelligence engineer is US$116,540 (Glassdoor).

There are some of the top artificial intelligence certifications, which are designed to further develop the knowledge and skills in the field of AI. One such certification is Artificial Intelligence Engineer (AIE™) certification from the Artificial Intelligence Board of America (ARTiBA). In this certification program, registrants can learn the several concepts of ML, supervised and unsupervised learning, NLP, cognitive computing, reinforced learning, and deep learning.

sharma niti

Leave a Reply

Your email address will not be published. Required fields are marked *