An artificial intelligence engineer is a person who uses traditional machine learning techniques, such as natural language processing and neural networks, to build models that power AI-based applications.
AI engineers help address the complex design challenges that result from combining the logic found in traditional applications with the learned logic from machine learning models.
A certification course in Data Science, Machine Learning, or Artificial Intelligence is highly recommended for those interested in becoming AI engineers. With these certifications, you will be able to enhance your resume and gain in-depth knowledge of AI topics, as well as increase your pay.
The main difference between data science and artificial intelligence (AI) is that data science is a broad discipline that includes the study of AI. AI is just one aspect of data science.
Programmers create mobile apps, operating systems, websites, and proprietary software for businesses and companies. AI engineers use traditional machine learning techniques and tricks, such as neural networks and natural language processing to implement and build models that run and require AI-based apps. In contrast, software engineers are responsible for maintaining and creating end-user systems. They are involved in both the hardware and software development process.
AI engineers have a big-picture view of an organization's AI operations. They are in charge of the AI platform, which provides services for customers while evolving the product according to the company's changing requirements.
However, machine learning engineers are expected to be subject matter experts in their sub-field, devise AI solutions, and apply the right solution to a problem. It's a more generalist approach that requires knowledge of several fields in AI.