AI Engineer

An AI engineer builds AI models using machine learning algorithms and deep learning neural networks to draw business insights, which can be used to make business decisions that affect the entire organization. These engineers also create weak or strong AIs, depending on what goals they want to achieve.
AI engineers have a sound understanding of programming, software engineering, and data science. They use different tools and techniques so they can process data, as well as develop and maintain AI systems.

Professionals who are finding how to become an AI engineer should also know about the skills required in this field. Some of them include:

Programming Skills

The first skill required to become an AI engineer is programming. To become well-versed in AI, it’s crucial to learn programming languages, such as Python, R, Java, and C++ to build and implement models.

Linear Algebra, Probability, and Statistics

To understand and implement different AI models—such as Hidden Markov models, Naive Bayes, Gaussian mixture models, and linear discriminant analysis—you must have detailed knowledge of linear algebra, probability, and statistics.

Spark and Big Data Technologies

AI engineers work with large volumes of data, which could be streaming or real-time production-level data in terabytes or petabytes. For such data, these engineers need to know about Spark and other big data technologies to make sense of it. Along with Apache Spark, one can also use other big data technologies, such as Hadoop, Cassandra, and MongoDB.

Algorithms and Frameworks

Understanding how machine learning algorithms like linear regression, KNN, Naive Bayes, Support Vector Machine, and others work will help you implement machine learning models with ease. Additionally, to build AI models with unstructured data, you should understand deep learning algorithms (like a convolutional neural network, recurrent neural network, and generative adversarial network) and implement them using a framework. Some of the frameworks used in artificial intelligence are PyTorch, Theano, TensorFlow, and Caffe.

Communication and Problem-solving Skills

AI engineers need to communicate correctly to pitch their products and ideas to stakeholders. They should also have excellent problem-solving skills to resolve obstacles for decision making and drawing helpful business insights.
Let us explore the career and roles in AI in the next section of the How to become an AI Engineer article.

90.000 EUR per year

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