AI has evolved in various sectors and has made the AI Engineer’s job one of the most popular professions in the technological field. Since the application of AI to increase organizational effectiveness, customer satisfaction, and decision-making has been on the rise, the need for AI experts has persisted. Whether you are a fresh graduate or a career changer, understanding the roadmap to becoming an AI engineer is crucial.
An AI engineer is supposed to create, develop, and integrate AI systems to solve various issues. According to the U.S. Bureau of Labor Statistics, employment in computer and information technology occupations, which includes AI roles, is projected to grow faster than other occupations from 2022 to 2032, adding about 377,500 new jobs each year, so it is high time to start a career in artificial intelligence. In this article, you will understand the AI engineer role, the essential skills needed, expected salary trends, and how to leverage AI certifications to advance your career.
Duties and Responsibilities of an AI Engineer:
The duties and responsibilities of AI engineers include writing code but also designing and developing ways to solve problems. AI engineers write intelligent algorithms that assist machines in learning from data and executing tasks that normally require human intervention.
Below are some of the primary duties of an AI engineer:
- Developing Machine Learning Models: Machine learning models are built by AI engineers for some particular business issues. These models may use supervised, unsupervised, or reinforcement learning modes.
- Data Collection and Pre-processing: AI systems need large volumes of data to be fed into the system to enable the system to perform as desired in the context that it is designed to operate. AI engineers get data ready for modeling this may entail data cleaning, data transformation, and data reduction.
- Training and Optimizing Models: AI engineers are supposed to provide large data sets to machines to develop machine learning algorithms. They also optimize models to make them more efficient, this could mean that they loop through processes and tests.
- Collaboration with Data Scientists: AI engineers interact with data scientists, software developers, and other stakeholders to understand the needs of the business and then come up with AI solutions that fit these needs. It also makes the models as close to the real world as possible since the collaboration is with practitioners.
- Deployment of AI Systems: This means that models should be taken to the implementation stage. AI engineers are expected to interpret the machine learning models and then deploy them to enable them to provide real-time solutions to the business.
- Continuous Monitoring and Maintenance: The systems need to be monitored to determine whether they are functioning. They also have to monitor the model and tinker with the system if performance has declined.
Skills Needed to Become an AI Engineer:
The position of an AI engineer implies that one has some skills, namely, machine learning, programming, and data manipulation. Here are some of the essential skills:
- Programming Languages: The programming languages include Python, R, Java, and C++. Python is used in developing Artificial Intelligence because of the presence of its libraries like TensorFlow, and Keras and also frameworks like PyTorch.
- Mathematics and Statistics: Knowledge of linear algebra, calculus, probability, and statistics is sufficient to comprehend and build machine learning models.
- Machine Learning and Deep Learning: Some of the forms of ML and DL that the AI engineers should have some understanding of them they include the following; Neural networks, Support vector machines, and Decision trees.
- Data Analysis and Visualization: AI engineers should be able to work with large amounts of data and then give an outcome in a format that the other side would comprehend.
- Natural Language Processing (NLP): Understanding NLP is important for AI engineers who are involved in text or speech recognition systems development. NLP enables the machine to comprehend natural languages and to be aware of what is being said.
- Cloud Computing: Various AI solutions are deployed to the cloud and, therefore, experience in AWS, Google Cloud, or Azure is necessary.
- Soft Skills: AI engineers should be able to communicate with other teams and solve problems because they will be working with other teams of the project and should be able to translate technical issues to other teams.
AI Engineer: Eligibility -
- Bachelor’s Degree: The first step that anyone who wants to become an AI engineer must meet is to have a bachelor’s degree in computer science, data science, information technology, or any other related field.
- AI Certification and AI Course: The candidates have to master certain skills that can be useful in an AI project by enrolling in an Artificial Intelligence Course. It is recommended that the student take courses in machine learning, data science, and deep learning.
- Master’s Degree: However, it is not required for one to have a master's degree in Artificial Intelligence, machine learning, or data science, but it is recommended and offers more chances in the present job market.
- Online AI Courses: To keep updated with the trends, nearly all working people take online AI courses. These programs offer projects and are quite beneficial for getting an idea and building a portfolio.
- AI Certification Programs: Having an AI certification can indeed help you get a better chance of being hired. Highly sought-after AI certifications include IBM AI Engineering, Google AI Certification, and Microsoft Certified: Azure AI Engineer Associate.
Salary Trends for AI Engineers:
AI engineering is among the highest-paying professions in the technology industry. According to Glassdoor, AI engineer earns around $118,000 per year in the US, and experienced AI engineers may earn more than $170,000 annually.
Not only in the United States, but AI engineers are also in high demand all over the world. For example:
- India: The pay that an AI engineer earns in India is roughly between INR 9 lakhs to INR 15 lakhs per annum. There are possibilities for experienced professionals to earn more than INR 30 lakhs per annum.
- United Kingdom: AI engineers in the UK earn an average of £50,000 to £80,000 based on experience and the area of expertise.
- Germany: AI engineers in Germany are paid an average of €60,000 to €85,000 per year.
This is because AI specialists are rare in the market and businesses are increasingly applying AI technology to create new solutions and sustain a competitive edge.
AI and Career associated with it:
AI engineering enables professionals to work in different positions in the sphere of AI. Some popular careers in artificial intelligence include:
- Machine Learning Engineer: These professionals are more or less engaged in the creation and deployment of machine learning models. This is one of the most promising AI fields of work.
- Data Scientist: Machine learning and statistical analysis help data scientists to find meaning in data. Occasionally, the AI engineers are involved in the development of the models.
- AI Specialist: AI implementers are employed in an attempt to ensure that the integration of AI solutions into the existing systems is well done. They are knowledgeable in some domains like NLP (Natural Language Processing), computer vision, or robotics for instance.
- AI Researcher: AI researchers are involved with improving the procedures and tools of artificial intelligence. They discuss new trends on how to improve machine learning algorithms and artificial intelligence systems.
- Robotics Engineer: Robotic engineers employ artificial intelligence to allow the robots to work independently in the production, medical, and transport sectors.
Why Seek an AI Certification?
AI certifications are designed to equip learners with the practical and theoretical knowledge that they require in the concept area. Here are some of the benefits of pursuing an AI certification:
- Career Advancement: An AI certification proves to a potential employer that you are capable of handling a particular job, and that makes you a good catch. This is especially the case in a market where there is high demand for talent and low supply, a certification will do a lot.
- Structured Learning Path: Another benefit of learning AI through certification programs is that it is a structured program that teaches areas such as machine learning, neural networks, and data analysis.
- Practical Experience: As it has been noted, almost all the AI certification programs include actual projects, and thus, the learners gain practical experience. This practical knowledge is very useful when it comes to constructing a portfolio for potential employers.
AI Certification FAQs:
1. Is an AI certification beneficial for a job?
Yes, an artificial intelligence certification can be very useful for your career particularly if you are interested in working in the AI field or if you are looking to level up. Certifications are highly appreciated by employers because they are evidence of the person’s proficiency in the AI technologies.
2. Is the ML/AI field a good field for the long term?
Yes, AI and machine learning are good long-term propositions. There should be high demand in the future for AI professionals since AI is being integrated into businesses and organizations and since the technology is advancing. LinkedIn said that AI Specialist is among the three new jobs in the global market for three years in a row.
3. What should I do to advance in my career with the help of AI tools?
For anyone who wants to develop a career in AI, one has to begin with the basics of computer science and programming. Take an AI course or certification to know more about areas of interest such as machine learning, NLP, and data analysis. Other ways of increasing the career include working on projects, participating in hackathons and building up the portfolio of AI skills.
4. What are the factors that compel a person to undertake artificial intelligence course?
An Artificial Intelligence Course is a good way to learn about the concepts in Artificial Intelligence and how to apply them. These are general courses that introduce subject matter that is relevant in engineering of AI such as machine learning, deep learning and AI model deployment.
5. Is it possible for the student to get a job after the completion of the applied AI course?
As for some of the applied AI courses, the students are not guaranteed job placements after the completion of the course. But they do assist you in the sense of employment since they equip you with practical skills, exposure and portfolio of AI projects which are deemed useful by employers.
Become AI Engineer: Conclusion
AI engineering is one of the highly sought-after careers of the today's technology-driven world where the use of tech is on the rise. Since AI is being incorporated in almost every field, jobs in AI are not only well paid but also the person gets opportunity to learn and innovation. Hence, anyone with an AI certification or a structured Artificial Intelligence Course is in a better position to prove his or her worth in the field and benefit from the many opportunities available in this promising field.
If you want to be an AI engineer and if you are interested in developing the next generation of machine learning algorithms or applying AI to real world problems, the journey to becoming an AI engineer is filled with possibilities. Talk to our team at Vinsys now!