Artificial intelligence engineers are the ones responsible for creating the programs that make up AI. Artificial intelligence developers find and pull data from an assortment of sources, make, create and test AI models and afterward use application program interface calls or inserted code to construct and carry out AI applications.

AI is used by many technology companies to automate processes and/or process large amounts of data efficiently. Developers that work on such projects at these companies are exceptional programmers, who have additional expertise in researching and designing AI systems that simulate human intelligence.

For someone to be successful in AI they must be proficient in data designing, data science, and programming.

AI Development Team
A typical AI development team will generally comprise the following elements.

Data Team - responsible for processing and analyzing the data.

Algorithm/Research team - consisting of Deep Learning and ML Engineers, drives the development of your AI’s foundation.

Infrastructure/Platform Team - building, maintaining, and scaling the software infrastructure.

Application Team - responsible for creating applications that customers interact with.

Skills Required
To be successful, it is essential for AI developers to be skilled in a range of disciplines including math, and programming languages such as Python, R, Java, C++, Scala, etc. Use of mathematical concepts, and programming languages help AI coders to develop complex and efficient algorithms. Other examples of skills needed include:

Algorithms and Mathematics
First and foremost AI developers should be familiar with how the algorithms work, how they are generated, and how they may be improved. They need to have an aptitude for solving complex math equations, and coming up with intricate algorithms.

Statistics and Probability
AI uses statistics and probability to detect the patterns and trends using a variety of models. Having a good grasp of probability and statistics is quite important for AI developers. In order for their AI outputs to be successful AI developers should be well versed in many statistical tools and probability concepts.

Coding and Technical Skills
Other technical skills AI engineers must have are:
Strong programming skills
Data Science
Statistics and probability
Data Engineering
Exploratory data analysis

AI Developer Roles and Responsibilities
Some of the most common responsibilities of AI developers may include:

Using AI software to solve problems.

AI system design, development, implementation, and monitoring.

Explain to project managers and clients the capabilities and limitations of artificial intelligence systems.

Create a data ingest and transformation architecture.

Keep an eye out for emerging AI technology to integrate into your company.

Other responsibilities may include:

Building AI models with the help of machine learning algorithms to acquire valuable business insights.

Carrying out statistical analysis and interpreting the results, and implementing the learnings from the data.

Programming networks to create AI models to solve complex tasks.

Performing maintenance on AI infrastructure.

Common Job Titles
Common AI job titles include:

Machine Learning Engineer - A machine learning engineer is at the heart of AI initiatives and is appropriate for those with a background in applied research, data science, and programming.

Data Scientist - Data scientists develop algorithms, collect and clean data for analysis. Then they analyze and interpret that dataset using machine learning and predictive analytics.

Big Data Engineer - They frequently collaborate with data analysts and data scientists. Big data engineers are critical in establishing an ecosystem that allows business systems to connect with one another and collect data.

Industries AI is revolutionizing
AI is helping automate industries from manufacturing to finance, businesses across multiple industries are using artificial intelligence to improve their processes. With AI technology continuing to evolve, a lot of industries will see a radical transformation in the coming years. To name a few:

Education - innovating teaching and learning practices.
Medical Testing And Diagnosis - medical decision making, automation, and workflows.
Carbon Emission Reduction - improving energy efficiency, monitoring carbon footprints.
Cybersecurity - learning, and adapting to new cyber crimes.
Hospitality - personalizing services.
Human resources - using artificial intelligence for employee engagement

Hiring AI Developers
Knowing what type of AI skills you're looking for before you can actively search for developers, will save you time and effort. Also, it's important you write an effective job description to attract good candidates. A good job description should clearly describe the kind of AI skills and experience the company is looking for, and be transparent about pay and work culture. This will help attract engineers and developers who are most likely to be interested in getting hired by your company.

If you’re looking to hire AI developers in 2023 here is a well put together in-depth guide to sourcing higher-quality AI candidates.This guide contains the full process of sourcing and hiring AI engineers.