Roles in an Artificial Intelligence Team.

The size and features of an AI team depend on the level of maturity, responsibilities, and value provided in each case.

In an initial phase, it is perfectly valid for all AI responsibilities to fall on a single person or even a part-time external consultant. Over time and with successes, the dimensions of the AI team will grow in the direction we describe below.

A mature, fully-functioning artificial intelligence (AI) team will have a variety of roles to ensure that all facets of the work are properly addressed. There is no one-size-fits-all format, but when designing the features of your own AI team, it may be helpful to know the following roles and their responsibilities:

AI Director (AI Manager, Chief AI Officer).

This role is essential to ensure that AI projects align with the company’s needs and objectives. The AI Director is a professional with hybrid technical and business knowledge who plays a crucial role in deciding what to build – evaluating what is technically feasible and what will bring value to the business – as well as in planning, managing, and monitoring AI projects.

Data Scientist (Data Analyst).

The Data Scientist focuses on examining and analyzing data to provide valuable insights that can lead to the decision to develop AI solutions or products.

Data Engineers.

Data Engineers are responsible for storing, organizing, and protecting data, ensuring they are available and in a suitable format for analysis and ML model training.

Researcher / ML Scientist.

These are the experts who research and apply the latest innovations in the field of machine learning. They work at the forefront of AI, experimenting with new techniques and approaches to improve existing models and solutions.

ML Engineer (Machine Learning Engineer).

The ML Engineer specializes in the development and application of machine learning models. These professionals translate the model prototypes developed by researchers or ML scientists into practical and efficient applications.

Traditional Software Engineers and DevOps.

These professionals focus on the development of conventional software solutions. Even though they don’t work directly in creating AI models, their work provides the infrastructure and applications that surround and support these models.