Pursuing a career as an Artificial Intelligence Engineer can be highly rewarding. This field has numerous perks and career benefits. They include high demand, high earning potential, rapidly growing area, impact, innovation and so much more. A career as an artificial intelligence engineer offers the opportunity to progress in cutting-edge technology. Additionally, it provides professional fulfilment and financial benefits.


Artificial Intelligence(AI) engineers are in high demand. Artificial intelligence can simplify the jobs that humans do such as speech recognition, business process management and even disease detection. AI engineers create models by combining machine learning algorithms and deep learning to get business insights that affect an entire organization. These engineers can construct weak or strong AIs. AI engineers must have a sound understanding of programming, software engineering and data science.


Pursuing a career as an artificial intelligence engineer requires one to be technically inclined and have a strong background in software programming. In this piece, I will guide you through the steps and requirements needed to start a career as an artificial intelligence engineer.


How to Become an Artificial Intelligence Engineer

  1. Obtain an O’level Certificate

    The first step to take when pursuing your career of interest is to obtain an O’level certificate. You need to have a solid foundation in science subjects such as chemistry, physics, mathematics and computer science. Additionally, you should have a minimum of credits in these subjects in your O’level examination. You will have a firm foundation to build your subsequent studies.

  2. Earn a Bachelor’s Degree

    You can obtain a bachelor’s degree in a computer-related course such as computer science, mathematics, physics, statistics, information technology or computer engineering.  A bachelor’s degree will provide you with a solid core knowledge of computer and technology subjects. Additionally, you will be able to work on AI-related projects, which will help you gain expertise before entering the field.

  3. Develop Technical Skills

    You should develop programming skills as it is essential for working with AI and machine learning. You can start by learning programming languages such as Python. You can also get familiar with libraries such as tensor flow, pytouch or sci-kit-learn.

  4. Consider Online Courses and Bootcamps

    You can also attend a boot camp or use a variety of online resources to learn about AI and machine learning. You can use websites such as Coursera, edX and Udemy. Additionally, there are also YouTube channels and blogs you can utilise.

  5. Acquire Practical Experience

    You can get practical experiences through internships, volunteering and entry-level jobs. This experience will give you practical knowledge on how to implement AI solutions in various ways and help you build a stronger resume.

  6. Work on Practical Projects

    Working on practical projects is vital in AI and machine learning. You should undertake hands-on projects to apply the knowledge you have gained.

  7. Build your AI portfolio

    Your AI portfolio is an effective tool that showcases your abilities and experiences. You should have a portfolio that will show the projects you have worked on, your skills and expertise.

  8. Pursue a Master’s Degree

    You can pursue a master’s degree in AI engineering to have a competitive advantage in this field. This can also boost your income potential. Additionally, it can give you a thorough understanding of and give you specialised technical skills. You can pursue a master’s degree in artificial intelligence engineer.

  9. Join Professional Associations

    You can join forums, online communities and social media platforms to interact with professionals and experts in this field. Furthermore, this will enable you to get access to knowledge and trends in this field.

  10. Consider Getting a Mentor

    An experienced professional in this field can provide helpful insights and analyse your strengths and other areas for development. Additionally, they can help you learn how to become an AI engineer and steer your professional path.


Skills Required to Become an AI Engineer

  1. Programming Skills
  2. Linear Algebra, Probability and Statistics
  3. Spark and Big Data Technologies
  4. Algorithms and Frameworks
  5. Communication Skills
  6. Problem-solving abilities
  7. Domain Expertise
  8. Time Management
  9. Teamwork
  10. Business Intelligence
  11. Critical Thinking


Areas of Specialisation in Artificial Intelligence Engineering

  1. Machine Learning Engineer: Machine learning engineers use massive amounts of data to construct prediction models. Additionally, they have expertise in machine learning, deep learning and deep learning frameworks.
  2. AI Developer: An AI developer collaborates with mechanical and electronics engineers to design software for computerised robots. They also build medical prosthetics such as an electronic arm or leg.
  3. AI Architect: They partner closely with clients to offer beneficial company and technological integration services. They are also in charge of designing and maintaining the overall architecture.
  4. Business Intelligence Developer: They are in charge of creating, modelling and analysing complicated data to discover business and market trends.
  5. Data Scientists: These professionals use machine learning and predictive analytics to gather, clean, analyse and understand vast complicated datasets.


In Conclusion, while starting a career as an artificial intelligence engineer, you must understand which industry you want to work with. Several industries use AI such as healthcare and education. As a result, there has been exponential growth in career opportunities within the field of AI.


Starting a career as an artificial intelligence engineer will launch you into an ever-developing field of exciting career opportunities. AI engineering is a rapidly expanding field. It can give you fresh challenges and intriguing professional development opportunities. However, this career path requires you to have the educational requirements and technological skills needed. Therefore, you should dedicate yourself to learning and acquiring the relevant skills.


Good luck!

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