An AI developer is nothing without a good command of programming languages. Your coding skills, to put it plainly, will determine your chances of landing a well-paying job at the desired company – and climbing the career ladder.

If you don’t know where to start, consider these five programming languages that AI developers from S-PRO, an AI/ML and data science company, rely on in their daily work.

Python

Python is popular for an AI systems tech stack because of its simplicity and flexibility. It is used to build data processing systems, train AI models to identify patterns in data, and create predictive analytics applications.

Developers across domains love Python for its simplicity and gentle learning curve, so much so that Python was named the most desired programming language by the 2024 Stack Overflow Developer Survey.

To use Python for AI development, you’ll need to have a good grasp of its frameworks and libraries like:

• TensorFlow and PyTorch for machine learning and deep learning models
• NumPy for computations and array operations
• Pandas for streamlined data manipulation and analysis using dataframes
• Scikit-learn for ML tasks like regression and classification
• Matplotlib for data visualization

R

Although R is not among the most widely used programming languages (only 4.3% of developers work with it), it’s essential for building AI systems requiring strong statistical capabilities. This language is designed for advanced data analysis and visualization, machine learning applications, and complex statistical modeling.

You’re most likely to work with R if you land a researcher or data scientist job. That said, developers may also need to be familiar with R to build artificial intelligence applications with advanced computations and visualization requirements.

Julia

Julia is a relatively new programming language, first available in 2012. (By comparison, both Python and R were created in the 1990s.) It was designed to power quick data processing operations and complex computations, making it an excellent choice for AI solutions in finance and scientific research.

So, AI systems that require high processing speed for complex calculations are typically written in Julia. Thanks to just-in-time compilation, Julia’s performance speed is similar to that of C++. Julia also supports linear algebra operations and parallel computation.

Java

Developers tend to pick Java for building large-scale cross-platform AI applications, all because of Java’s high interoperability capabilities. Put simply, Java applications can be easily integrated with AI libraries to power AI features and adapt the solution to deployment on multiple platforms.

Besides mastering Java itself, you’ll need to get well-acquainted with its key AI packages and libraries. The most popular ones are WEKA, Deep, H2O, Deeplearning4j, and Smile.

Scala

Scala is a language that supports both object-oriented and functional development approaches. This flexibility is one of the main reasons why Scala is favored by AI developers who work on complex AI systems.

In addition to this flexibility, Scala works seamlessly with Apache Spark, a large-scale data processing engine. (Apache Spark is commonly used for model training and is written in Scala.) Scala is also highly compatible with a number of Java libraries and is relatively easy to use thanks to its clean syntax.

Other Crucial Skills for Aspiring AI Developers

Mastering these programming languages is a must if you want to land a job as an AI developer, but the list of required skills doesn’t stop there. In addition to learning the ins and outs of Python, R, or Java, you should also develop your skills in:

• Mathematics and statistics
• Data management
• Version control (e.g., Git)
• Big data analytics
• Data visualization

On top of that, employers are always fishing for solid soft skills, too. In fact, 56% of job seekers report that their soft skills helped them find a job, right after certifications and tech skills. The most in-demand soft skills include:

• Problem-solving
• Communication and collaboration
• Curiosity and creativity
• Critical thinking
• Attention to detail
• Ability to work under pressure

Final Thoughts

Python, R, Java, Julia, and Scala are just five of the top programming languages for AI developers. Other popular languages that didn’t make the cut are C++, JavaScript, Lisp, Haskell, and Mojo.

Need expert help to choose the right programming language for your AI project? Discuss your future solution with S-PRO, an AI and data science IT consulting company with 10+ years of experience.