Artificial intelligence is one of the highest demanding fields. It includes general AI, expert systems also known as data mining, machine learning, Neural Networks, and lastly, fuzzy systems. These have been essential and interesting topics among students, scholars, faculties as well, and professionals.
Since AI has provided enough information to the public, we can then use this article to inform the upcoming generation to be more knowledgeable about the career opportunities relating to this domain. AI is all about Machine learning and deep learning which involves three major steps including Identifying data sources, creating a system to analyze that data, and making final decisions based on the analyzed data.
Let’s talk about the various career opportunities in the field of Artificial Intelligence. Before reading this article, you should also check the exact difference between AI, Machine Learning, and Deep Learning.
Contents
Career opportunities in Artificial Intelligence
1. AI Research Scholar
Being a research scholar is one of the highest demanding career opportunities in AI. AI and other related terminologies are new terms to society. Several requirements need to be met to be a research scholar on AI. The area of focus will be on research improvements to machine-learning algorithms.
Often research scholars are appointed by governments to provide a solution to real-time problems. Sometimes, they need to combine one or two domains as a way of applying real-time problems to new domains as well as technology.
Requirements:
- Have a Ph.D. in the related field of general AI though these positions are rare to find but are always restricted to experienced Ph.D. researchers and hand-picked team members.
- Be innovative and prove your logical thinking regarding the field. You should be able to provide innovative ideas to help solve real-time problems.
2. AI-Based Software Development
AI Knowledge for software has become an essential requirement since most tools have included AI in them. Software engineers are appointed based on their ability to think innovation and problem-solving skills.
Requirements:
- A bachelor’s degree in a related field such as Computer Science. Having a good understanding of AI and machine learning as well as good mathematics skills will be an additional advantage.
- Master’s degree in related fields and have a good research background in Research publications in both National and international Journals.
3. Data Scientist
Data has been considered gold since it can be used to predict the future of a business by many organizations. Even though most of the predictions have been made from the generated data in the internet, they are still considered to be important for your business. People involved in these tasks are referred to as data scientists.
Requirements:
- A good understanding of data structures as well as statistical mathematics.
- Though a Ph.D. in a related field is needed some individuals have evolved with just a bachelor’s degree.
Data science is still a new job opportunity in the market but in the next 5 years, it will be among the predominant job opportunities in tech companies for graduates.
4. Machine Learning Engineer
Machine learning involves applying a machine learning or even AI framework to a certain problem though in a different domain. This is one of the essential parts of AI. according to a Forbes Technology 2017 article, Machine learning was considered to be a vital and peak domain. It involves Gesture recognition, Ad analysis, fraud detection, etc. Machine learning engineers understand the machine’s nature and help solve problems related to society.
Requirements for ML engineer;
- A good mathematical knowledge
- A good understanding of the systems of the hardware.
Since the industry is moving towards AI, there is a high demand for machine learning engineers due to the scarcity of individuals specialized in this field. To showcase your expertise you can follow this machine learning engineer resume. Additionally, if you’re interested in expanding your knowledge, you can check out this Free Machine Learning Course offered by Google.
5. Automation Engineer
Automation engineering is a new area of specialization in Artificial Intelligence. it involves using AI to enable human engineers to solve various problems right from simple to more complex problems. Since these engineers understand the nature of the environment, they can automate the commonly repeated tasks that often do not require human engineers’ support.
Importance of automating tasks;
- Automating these tasks enables AI tools to assist human engineers as well as organizations to meet their demands on time using a limited number of resources.
- It helps reduce human effort regarding tasks that do not need a human presence.
Conclusion
To be successful in the AI domain, you are required to have good mathematics knowledge, have a sturdy foundation on system software, algorithms, and data structure. In addition, you should have adequate skills for problem-solving, programming, and learning.
The Information about career opportunities was extracted from various job listing sites and government job openings
