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Artificial intelligence or AI is a much broader field involving incorporation of human intelligence into machines. So that they are able to involve in self processing, self-learning, self-thinking and self-correcting. The key objective of using artificial intelligence is to let the systems function on their own without any requirement of coding for every logic. To have a rewarding career as an AI engineer. One needs to go for a comprehensive AI certificate course and have certain basic skills such as knowledge of Data Science and Statistics, and basic understanding of data processing. In addition to this, every AI engineer must have certain other major skills, which will be discussed broadly in this article.
Skills needed to become an artificial intelligence engineer
The basic skills required for becoming an Artificial intelligence engineer are:
- Data Analytics: To be efficient at developing deep-learning models that help in analyzing patterns, a strong knowledge of data analytics is a must. Being good at analytics will be required for testing and configuring AI.
- Applied Mathematics: One who aspires to be an AI engineer should love mathematics as it forms the core of AI. A deeper understanding of quadratic programming, gradient descent, and convex optimization is a must.
- Statistics and Algorithms: In addition to having the knowledge of applied mathematics. Having a deeper understanding of statistics is essential for working with algorithms. Prospective AI engineers need to have a profound understanding of probability, standard deviation, and models such as Naive Bayes and Hidden Markov.
- Fluency in Programming Languages: To be a successful artificial intelligence engineer, you need to be good at several programming languages such as Python, Java, C, and C++, to name a few.
- Great Communication and Problem Solving Skills: Artificial intelligence often needs innovative usage of ML models and creative thinking. Furthermore, you should be able to communicate your ideas to your teammates who may require additional knowledge on AI problem solving.
- Knowledge of Neural Networks: Being an AI engineer, you will be required to be efficient at neural networks. Neural networks are software’s that function just like human rain and help in pattern recognition, classifying images, and solving complex problems. Given the fact that AI engineers spend considerable amounts of time with neural networks, profound knowledge of the subject is a must.
- Team Management: Apart from having technical knowledge, the ability to manage a team also matters for an AI engineer. This helps AI engineers to easily communicate their ideas to their teammates and get things done in a more systematic manner with high efficiency.
- Knowledge of Cloud: As an AI engineer, having a basic idea of the cloud will help you manage the storage space well and identify the storage system that will best suit your project requirements.
Salary of an artificial intelligence engineer
After taking up AI engineering, you can take up the following job roles for which the salary is mentioned in the table below:
| Job Title | Salary Range | Salary Average |
| Software Engineer | $65,000-$145,000 | $96,097 |
| Data Scientist | $78,000-$144,000 | $115,020 |
| Senior Data Scientist | $99,000- $163,000 | $129,494 |
| Lead Data Scientist | $98,000-$188,000 | $148,547 |
| Senior Software Engineer | $97,000 – $167,000 | $131,706 |
| AI Specialist | $108,000 – $254,000 | $135,238 |
| AI Researcher | $105,000- $245,000 | $133,500 |
Source: PayScale.com
Gartner, Linkedin, and Forbes have acknowledged AI as one of the top emerging job roles in this era. Thus, seeking a career in AI can be highly rewarding and one of the smartest career moves. However, to have a flourishing career in AI, it’s essential to focus on acquiring the skills discussed in this article. So, don’t wait and pull up your socks to become a skilled AI engineer and allow yourself to explore a variety of career opportunities ahead.