What are the jobs of the future? Artificial intelligence is one of the most promising today. Recent graduates from the programs for artificial intelligence and machine learning enjoy a high rate of employment. Their salaries are among the highest on the market. Moreover, they are creating products that are truly changing the world. 

Which occupation should you choose? Let us look at some of the most in-demand jobs in AI.

What are the in-demand professions? 

The best way to learn what professions are in-demand right now is to go on job hunting websites and study open job ads or read research made by the same companies.

Indeed.com reports about a huge demand growth for the following professions: 

• Machine Learning Engineer – 344%;
• Robotics Engineer – 128%;
• Computer Vision Engineer – 116%;
• Data Scientist – 78%.

Let us have a more detailed look at each of these professions. 

Machine learning engineer

Machine learning is a subset of artificial intelligence that studies how to build algorithms that can learn from data. Machine learning and deep learning are used in a wide variety of fields to solve problems from prediction and natural language processing to computer vision. The best courses to study machine learning you will find here.

A machine learning specialist deals with:

• creation of ML algorithms that help computers to acquire the ability to self-learn; 
• research, analytics, and the identification of valuable features for building an algorithm;
• constructing artificial neural networks. Such algorithms independently analyze and highlight the features that an object has and structure them (for example, sorting and analyzing content: images, texts, audio recordings).

Robotics engineer

Robotics engineer is engaged in the design, construction, development and operation of various ML-powered machines, mechanisms, and technical equipment.

Depending on the specialization, the functions of a mechanical engineer can be:

• development of technological schemes, sketching and constructing mechanisms and parts of mechanisms;
• maintenance: condition monitoring, repair, adjustment, etc.;
• testing, an examination of equipment safety.

Computer vision engineer

A computer vision engineer is a specialist who develops and implements computer vision algorithms used for object recognition, video analytics, image and video content description, gesture and handwriting recognition, and intelligent image processing.

Computer vision is a technology that enables machines to track, classify, and identify objects by extracting data from images and analyzing it.

Depending on the scope of the company, the tasks of a computer vision developer may include:

• development and implementation of algorithms for classification and recognition of static and/or dynamic objects;
• selection of the necessary tools, libraries, and components for development;
• optimizing tracking performance;
• applying machine learning technologies or libraries to improve detection and display quality indicators;
• solving client-server problems and improve or refactoring of the current codebase.

Data scientist

A data scientist is engaged in:

• Big data analysis; search for possible patterns in the data array; predicting trends based on the data received (for example, customer demand).
• Storing, processing, and providing access to data.

Here is what a data scientist has to be able to do:

• Program in Python since it is the most popular data science language;
• Visualize data – design dashboards or interactive infographics.
• Work with libraries and databases. Learn to work with Pandas, NumPy, and Matpotlib libraries and master PostgreSQL, SQLite3, MongoDB databases.
• Apply neural networks to solve real-world problems. Learn how neural networks work for computer vision and linguistics tasks.
• Build machine learning models using different algorithms for regression, classification, and clustering.
• Create recommendation systems. 

Conclusion

There are many interesting professions in the field of AI. Regardless of what you choose, you will follow a fascinating and well-paid career path. However, in order to succeed in any of these professions, you need to have a strong mathematical background, coding skills, and the ability to process and analyze a lot of information.