Artificial intelligence can improve and simplify a variety of tasks, including speech recognition, business process management, image processing, and even disease detection. If you are already tech-savvy and have experience with software development, you might want to learn how to become an AI engineer to pursue a lucrative AI career.
What is artificial intelligence?
Artificial Intelligence refers to a computer system’s ability to mimic human behavior. Machines exhibit this form of intelligence, which can be compared to the natural intelligence expressed by people. These machines learn from previous data and behaviors, both good and poor. With this new information, the system can correct itself to prevent errors from occurring again, as well as make any necessary adjustments to handle new inputs. Finally, the computer is capable of doing tasks that are comparable to those performed by people.
We will look at what an AI engineer does and what is the scope that the future holds for these professionals.
What are the roles and responsibilities of an AI engineer?
As an AI engineer, you must create, test, and implement AI models using programming algorithms such as randomized forest, logistic regression, and linear regression, among others.
Among the roles and responsibilities are:
- Convert machine learning models to application programming interfaces (APIs) so that they can be used by other programs.
- Create AI models from the ground up and assist various parts of the company (such as product managers and other stakeholders) in understanding the model’s outcomes.
- Conduct statistical analysis and fine-tune the data so that the company can make more informed judgments.
- Be an excellent team player, as collaborating with others is essential.
What are the skills needed to become an AI engineer?
Professionals interested to be artificial intelligence engineers should be aware of the abilities required. Among them are the following:
Skills in programming
Programming is the first skill needed to become an artificial intelligence engineer. Learning computer languages like python, C++, Java, and R to construct and implement models is essential for becoming well-versed in AI.
Probability, statistics, and linear algebra
You will need a thorough understanding of linear algebra, probability, and statistics to comprehend and build AI models like Gaussian mixture models Naive Bayes, Hidden Markov models, and linear discriminant analysis.
Technologies such as Spark and big data
AI engineers work with terabytes or petabytes of data, which might be streaming or real-time production-level data. To make sense of enormous data, these engineers will need to be familiar with big data technologies, machine learning algorithms, and Spark. Other big data technologies, such a Cassandra, Hadoop, and MongoDB, can be used alongside Apache Spark.
Problem-solving and communication skills
To pitch their goods and ideas to stakeholders, AI developers must communicate effectively. They should also have good problem-solving skills in order to overcome roadblocks in the process of making decisions and gaining useful business insights.
Let us take a closer look at the salary element of AI engineering, which is the most important selling point for aspiring AI engineers.
How much does an AI engineer earn?
According to Glassdoor, the average annual income of an artificial intelligence engineer in the United States is USD114,121. In different organizations, salaries vary depending on experience and knowledge.
Tip for potential AI engineers
Even if there is a skill gap and corporations are looking for these engineers, it is important to remember that AI developers and engineers must be highly skilled in order to land jobs with Fortune 500 companies. If you are looking for a job like this, you can get certifications to improve your skills and learn more about machine learning algorithms and other AI tools and technologies. Some artificial intelligence certifications to go for are: