The future is being shaped by the integration of both engineering and artificial intelligence (AI). AI engineering roles are sitting at the forefront of revolutionary change in this digital era, providing individuals with unmatched chances to develop ground-breaking solutions and expand the realm of possibilities. In lieu of this, there has been a trend towards hiring qualified AI engineers. A trend observed not only in engineering but across other sectors as well, including healthcare, finance, and many others. This suggests a plethora of prospects in the field of artificial intelligence for engineers.
In this article, the jobs and opportunities available will be explored, as well as the competencies required to thrive in this exciting and leading edge sector.
Job Opportunities
Artificial intelligence (AI) has become a driver of change in engineering by creating immense employment opportunities for engineers working in various spheres. However, to tap into these opportunities, individuals and engineers have to be adept with the appropriate engineering expertise.
Machine Learning
Among the roles in AI engineering that are most sought-after is machine learning. An industry anticipated to be at the top of the list in the next 4 years. Engineers specialising in machine learning create, construct, and implement models capable of analysing large volumes of data while carrying out evaluations and system optimisations based on the inferences drawn. In order to be eligible for this role, aspirants are required to be sound in mathematics and computer science. Having a decent background in programming and statistics is also essential.
Data Scientist
The next occupation is that of a data scientist, whose role is similar to that of a machine learning engineer. One of the key roles played by data scientists is to gather, analyse, and interpret/visualise large volumes of data, which helps business leaders make sound decisions. It should be known that data science is one of the most saturated fields in the world today. Hence, to be able to make waves and remain relevant in this role, it is essential to be proficient in statistics, machine learning algorithms, and data visualisation techniques. Major programming languages like SQL and Python should also be part of your skill set.
Software Engineering
Next is software engineering. Software engineering is different from the others in the sense that it has what seems like a symbiotic relationship with AI. In the creation and maintenance of AI systems, software developers are essential. At the same time, AI helps automate certain tasks that software engineers traditionally complete. Hence, competencies associated with this role are unlike others, as SE is all encompassing. Aspirants are required to be adept in a number of programming languages, such as Python, Java, or C++, for algorithm development and software implementation. A thorough understanding of machine and deep learning is also imperative, followed by data processing and structuring, mathematics, and statistics.
AI Scientist
The members of scientific teams on artificial intelligence constitute another significant group of specialists in the AI engineering field. These scientists are always in search of new algorithms and techniques to upgrade and refine the existing AI tools. Skills needed for this role include a robust foundation in computer science, math, and machine learning, as well as experience with programming languages such as Java C++ and MATLAB.
In addition, there are expert roles in robotics, computer vision, and natural language processing (NLP) for AI engineers. NLP engineers develop the methods and systems that let computers comprehend, interpret, and produce human language. These roles call for proficiency with NLP libraries (such as NLTK and spaCy), mastery of machine learning methods for text processing, and an understanding of linguistics and language theory.
As regards robotics, the role of engineers is to create and develop robotic systems that use AI for sensing, control, and decision making. Competencies include mastery of robotics frameworks (e.g., ROS), experience with sensor fusion and localization techniques, and knowledge of AI algorithms for robotic perception and control.
Artificial intelligence engineering is much more diversified as a career than people imagine. Keeping up with the latest developments in AI technology, upskilling, and developing a fierce competitiveness in this opportunity-rich industry is of paramount importance.
How to get an AI engineering job
Aside the skills and competencies listed for the jobs discussed, there are other critical things to take into consideration;
- Obtain btain a degree or certification in a particular field of interest.
- Be familar and achieve competency in the various skills required
- Build a strong portfolio. This is done by showcasing personal projects on a portfolio website or GitHub to present skills and expertise. This serves as evidence to potential clients.
- Seek internships, co-op opportunities, or entry-level positions in AI-related fields to gain hands-on experience.
- Attend networking events, career fairs, and conferences to expand professional networks and explore job opportunities. Ensure these networking events align with preferred role, as they provide opportunities to meet industry professionals.
- Finally, the job search can start. Resumes and cover letters should be tailored to the preferred area of interest.
Highlights
| AI Engineering Roles | Average Annual Salary |
| Machine Learning Engineer | $162,740 |
| Data Scientist | $124,000 |
| Software Engineer | $120,112 |
| AI Scientist | $123,000 |
| NLP Engineers | $128,400 |
| Robotics Engineers | $85,936 |
