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Machine Learning Engineer vs. AI Engineer

Technology innovation has brought about new roles. In particular, the generation of big data has prompted computer scientists and data analysts to redefine their roles. Now, different types of experts have emerged to cater to various needs. Machine learning (ML) and artificial intelligence (AI) are newer fields, which gathering momentum. As such, engineers are emerging in both disciplines. Although these experts may perform similar tasks, their expertise diverges. Nontechnical individuals mostly do not see a difference between the two. This article will compare a machine learning engineer and an artificial intelligence engineer.

About a Machine Learning Engineer

A machine learning engineer is an expert that is concerned with the design and implementation of self-tunning AI systems. These systems usually automatically operate using predictive models. As such, an ML engineer is mostly occupied with the development of algorithms that learn and make predictions using collected data points. An ML engineer usually does not work in isolation. Instead, they work with a team of data scientists. In addition, the engineer also works with developers, sales, and other stakeholders within an organization. An ML engineer mostly tries to improve the work of a data scientist. They use ML tools to collect, analyze, and classify big data, which is used within the ML framework.

About an Artificial Intelligence Engineer

An artificial intelligence engineer is a specialist who creates algorithms that mimic human thinking, behavior, and decision-making process. This expert uses the techniques and tools available within the machine learning framework to develop AI models for AI applications. In particular, the AI engineer uses neural networks and natural language tools to achieve their aims. As such, the engineer is able to create various applications, which include language translation, dynamic advertising, and visual identification.

Comparing ML Engineer with AI Engineer

In general, these two specialists use machine learning tools. However, the models they develop are different. The difference between these two experts is discussed under the following subheadings.

Qualification and Skills

To become an ML or AI engineer, you will require some qualifications and skills. An ML engineer should have a degree in math, computer science, statistics, or related courses. Likewise, having a graduate degree is useful. Furthermore, an individual should be good at calculus, statistics, and linear algebra to excel in machine learning engineering. Other skills that an ML engineer should have include

  • Problem-solving skills;
  • Teamwork mentality;
  • Programming knowledge, especially proficiency in a few languages;
  • Understanding of computer operation;
  • Comprehension of software architecture, modeling, and data structuring.

On the other hand, an AI engineer should have a degree in computer science, math, statistics, cognitive science, or linguistics. In general, the qualifications and skills of an AI engineer are similar to that of an ML engineer. Nonetheless, an AI specialist should have the following skills.

  • Understanding of coding and programming languages
  • High level of creativity
  • Communications skills
  • Business and management skills
  • Ability to generate prototypes

In addition, a good understanding of human behavior is usually good for an AI engineer.

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