When hiring an AI developer, it is crucial to look for a blend of technical expertise and soft skills. Key technical skills include proficiency in programming languages like Python, R, Java, and C++, as well as familiarity with machine learning frameworks such as PyTorch, Keras, and TensorFlow.

An AI developer must understand machine learning algorithms, data preprocessing, feature engineering, and deep learning. Problem-solving, analytical skills, and knowledge of big data technologies are equally important.

Adaptability and a commitment to continuous learning are essential in this rapidly evolving field. Additionally, strong communication and teamwork skills are vital for effective collaboration with diverse teams and stakeholders.

In this post, we'll discuss the best qualities to seek in an AI developer so you can place the right candidate for your client’s needs.

Let’s get started.

Abilities to Consider in an AI Developer

The study of artificial intelligence (AI) is expanding quickly. Indeed, it has the potential to completely transform a number of industries, so the need for qualified AI developers is growing as more businesses use this technology.

In terms of hiring, it is critical to seek out certain abilities in a developer to make sure they can provide high-quality work. Here are the eight skills an AI developer must possess.

An Understanding of Programming Languages

A strong programming base is a must for every AI developer. They should be skilled in the Python, R, Java, JavaScript, and C++ programming languages, which are widely used in AI development. They should also be familiar with frameworks and libraries like PyTorch, Keras, and TensorFlow.

For example, a Python script is used for low-level computer interactions. Developers use Python to automate file operations, handle system tasks, and control hardware components, while C++ is used to write both high and low-level codes for system programming and game development.

Knowledge of Machine Learning Algorithms

An artificial intelligence (AI) system uses a collection of rules or procedures (called a machine learning algorithm) to perform tasks. This is most commonly used to find new patterns or insights in data or to predict output values based on a given set of input variables. Machine learning (ML) relies on algorithms to learn.

AI-ML developers must have deep knowledge of different machine learning techniques (including reinforcement, unsupervised, and supervised learning). They must be able to decide which algorithm is best suited to a particular task and carry it out successfully.

For example, the algorithms use reinforcement learning that is trained to make a series of decisions. In reinforcement learning, a programmer chooses what to do by following a policy. In turn, it gains knowledge from the results of these decisions by receiving rewards or penalties.

Data Preprocessing and Feature Engineering

Data is the backbone of AI. A skilled AI developer must be adept at preprocessing (i.e. modifying raw data to an understandable format) and cleaning data to ensure its quality and reliability. Data preprocessing includes handling missing values, scaling features, encoding variables, and reducing dimensions.

AI engineers should also be able to perform feature engineering, which involves selecting and transforming the most relevant features from the data to improve the performance of AI models. Feature engineering makes data easier to analyze.

Awareness of Deep Learning

The deep learning area of artificial intelligence deals with teaching neural networks to analyze large volumes of data in order to solve issues. To do this effectively, AI-ML experts must be adept with frameworks like PyTorch or TensorFlow.

Once trained, a deep learning algorithm can be used to predict new data. For instance, one can utilize a deep learning algorithm that has been trained to identify flowers in photos to recognize flowers in new photographs.

Problem-Solving Skills and Analytical Skills

The most important skill an AI developer should possess is problem-solving. It combines critical thinking, technical skills, and creativity. Candidates must be able to break down complicated problems into simpler parts and come up with workable answers.

Analytical skills include implementing certain habits and strategies to improve logical reasoning, critical thinking, and creative thinking. Developers, through artificial intelligence, intend to create machines and systems that can do tasks that usually require human intelligence.

Knowledge of Big Data Technologies

An AI-ML developer must understand big data technology. This includes data mining, storage, analytics, and visualization. In brief:

Data mining discovers patterns in large databases.
Data storage is the retention of information.
Data analytics is the process of examining, transforming, and modelling data to extract meaningful insights, make decisions, and identify patterns.
Data visualization is the process of representing data through images, graphics, and animations.

For example, observing client behavior and purchasing patterns to provide highly customized retail product recommendations for each customer are all part of big data technology. Through data mining, purchasing patterns are noted. Through data analysis, customized product recommendations are made for the customer. Also, to identify fraud in real-time, payment trends are tracked and compared to past consumer activity.

Constant Learning and Flexibility

Artificial intelligence (AI) is a constantly changing field, with new methods and tools appearing regularly. An enthusiasm for lifelong learning and the flexibility to adjust to new advances in the field are essential qualities of a competent AI developer. They must easily accept and adapt to these new technologies and possess a keen interest in the latest AI developments.

To improve their knowledge and abilities, they should read the most recent research, go to conferences, and take part in online forums.

Teamwork and Communication Skills

Working in versatile teams and coordinating with data scientists, domain experts, and other stakeholders are commonplace in the creation of artificial intelligence. Therefore, developers must have strong communication skills to interact with team members, understand their demands, translate words, and clearly explain algorithms.

An AI expert should have good teamwork and communication abilities to ensure quality project outputs and successfully communicate technical concepts to non-technical team members.

Hiring the right AI developer involves finding a balance between technical skills and soft skills. At Sourcedesk Global, we look for proficiency in programming, machine learning, and big data technologies. This is coupled with strong problem-solving abilities, adaptability, and communication skills that ensure the development of strong and innovative AI solutions. Sourcedesk Global helps companies both big and small to look for competent AI developers who possess all these qualities. Contact us to make the hiring process easier. Click on “Hire Developers” to fill out your needs or requirements.