In the past few years Artificial Intelligence has emerged as one of the fastest growing fields. AI is rapidly integrating itself into other industries and, in turn, creating lots of job opportunities. Artificial Intelligence is behind everything from powering virtual assistants to giving us self-driving cars and revolutionising industries such as healthcare, finance, and entertainment.
Today, in this article, we’ll discuss how to become AI engineer so that you can also take part in this technological revolution. We’ll discuss important steps, skills, and tools needed to start a rewarding career in AI.
Understanding What an AI Engineer Does
Before we discuss how to become AI engineer, it is important that we understand the job of an AI engineer. The job of an AI engineer involves developing, implementing and maintaining AI systems or mechanisms that imitate human intelligence. They are tasked to build efficient AI algorithm design models, and they experiment with machine learning models to help them create intelligent applications that are capable of learning from provided data and make necessary decisions accordingly. With the growing use of artificial intelligence in various industries, the need for AI engineers is also increasing rapidly. Some of the industries that require AIÂ engineers are robotics, healthcare, finance, and e-commerce.
Key Skills Required to Become an AI Engineer
There are some prerequisites that you need to fulfil in order to become a successful AI engineer. This involves both technical and soft skills that will help you to stand out in the field of Artificial Intelligence. So let’s have a look at them:Â
1. Programming Skills
Coding is one of the most important aspects of the career of an Artificial Intelligence Engineer. You’ll need to master programming languages such as Python and R. Python. As both of these languages are very dominant in the field of AI. The languages are very popular due to its simplicity, flexibility, and extensive library support for machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn.
2. Machine Learning and Deep Learning
Machine learning plays an important role it which comes to development of any AI model or related technologies. So, your understanding of machine learning is fundamental for AI engineers. You need to be well-versed in supervised learning, unsupervised learning, and reinforcement learning. Furthermore, you should also be comfortable in working with neural networks deep learning frameworks and have a good understanding of model training and evaluation.
3. Data Science and Analytics
Data plays an important role in the development of any AI model, and when it comes to data analysis, nothing comes close to AI models. So, in order to be successful as an AI engineer, your knowledge of data science skills are essential. You must be proficient in how to collect, clean, process, and analyse data to derive actionable insights.
4. AI Tools and Frameworks
It goes without saying that an AI engineer should be proficient with popular AI tools and frameworks such as TensorFlow, PyTorch, Keras, and Scikit-learn. As these frameworks and tools play an important role in building, training and deployment of various machine learning models effectively.
5. Mathematics and Statistics
A good AI engineer is proficient in mathematics and statistics. So, if you want to become an AI engineer, then you should also be proficient in topics such as linear algebra, calculus, probability, and statistics. This knowledge will help you in working with ML algorithms and AI models.
6. Problem-solving and Critical Thinking
In order to troubleshoot issues related to model performance, algorithm accuracy, and more, you’ll need to have strong problem-solving skills and critical thinking. The job of AI engineers is to solve complex problems using data-driven approaches.
Steps For How To Become AI Engineer
Now that we have discussed all the necessary skills that are required in order to become a successful AI engineer. Let’s discuss the roadmap for how to become AI engineer.
1. Obtain a Strong Educational Foundation
The IT industry is all about talent, however, a degree along with talent can make your entry into this field easy. Most of the AI engineering jobs around the world need at least a bachelor’s degree in the field of computer science, data science, mathematics, or related disciplines. Some higher roles may ask you for a master’s degree or even a Ph.D if it’s a position that requires heavy research. Moreover, if you’re already working in the industry, then getting a master’s degree in artificial intelligence or data science can be a great step up for your career. You can look into part-time or online courses for AI and ML offered by different universities around the world.
2. Build a Strong Programming Foundation
As we have discussed earlier, having a strong programming background is very important for your career as an AI engineer. As Python is the programming language for all AI development programs, learning Python from scratch is important. So, you’ll need to increase your proficiency in coding and improve the understanding of various AI libraries such as TensorFlow or PyTorch.
3. Practical Experience With Machine Learning
The next thing you’ll need to work on is your practical experience. Having theoretical knowledge alone is not enough in order to prepare AI solutions for real world problems. To get good experience you can start working on personal AI projects from your college days. This will help you in gaining practical exposure and build a portfolio. Furthermore, you can also join some part time or full time internships to gain more hands-on experience. You can create anything from creating a chatbot or a machine learning model for image recognition.
4. Master Deep Learning and Neural Networks
Deep learning and Neural Networks are an important part of computer vision and natural language processing. So, in order to create robust AI models, you’ll need to perfect your knowledge about neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs).
5. Work with AI Tools and Frameworks
Another thing that you’ll need to excel at is the AI tools such as TensorFlow and PyTorch. These frameworks and tools play an important time in building, training and deploying machine learning models. So, during your journey, make sure to get hands-on experience with these tools. You can do so by contributing to open-source projects, participating in hackathons, or completing online courses.
6. Understand Data Science and Analytics
Data is the core part of any AI model. So you’ll need to develop your data science skills such as data preprocessing, analysis, and visualisation. Furthermore, you should also have proficiency in various data analytics tools such as Pandas and NumPy.
7. Develop Soft Skills and Build a Strong Portfolio
Apart from technical skills, you’ll also need to develop some soft skills in order to grow in your career as an AI engineer. Soft skills, include problem-solving abilities, communication skills, and critical thinking, are a must in AI engineers. Furthermore, you should also build a portfolio that can showcase your projects, which would make you suitable for hiring by various tech companies. You can showcase your work on GitHub repositories and contribute to open-source platforms.
Career Path and Job Opportunities for AI Engineers
So, now that we have understood how to become an AI engineer let’s see what are the different career opportunities in the Artificial Intelligence field. There are a wide range of job opportunities that are available, but we’ll discuss some of the most prominent ones:
1. AI/ML Engineer
The main job of the AI/ML engineer is to implement machine learning models and algorithms. This includes data preprocessing, training of models and deploying these said AI/ML models in the various real world applications. Their job is to integrate AI into existing frameworks and automate manual tasks.
2. Data Scientist
Another job that you can look into is data scientist. The job of a data scientist includes doing mathematical and statistical analysis for data-driven decision making. Data scientists often work closely with AI engineers for data collection, cleaning, and analysis. This process is important for training AI models.
3. AI Research Scientist
The job of AI research scientist involves finding venues for new Artificial Intelligence models, improving existing algorithms and working towards contributing to the existing knowledge base of artificial intelligence. So this is something you can also look into.
4. Machine Learning Engineer
Another job in the field of AI that you can look for is the Machine Learning Engineer. These people are responsible for designing scalable ML models and deploying them into different industries. Furthermore, these ML models are of great use in natural language processing (NLP), computer vision, or reinforcement learning.
Average AI Engineer Salary Around the World
Now that we have discussed what are the different career opportunities as an AI engineer, let’s have a look at how good this career pays.
Artificial intelligence is a rapidly growing industry and lots of other industries are also adopting it rapidly. This is why the demand for talented AI engineers has skyrocketed, which makes it one of the most lucrative fields right now. So let’s see how much AI engineer earns in different parts of the world.
In the USA, an entry-level AI engineer earns around $120,000 to $150,000 annually. People with high experience or AI specialists easily earn over $200,000 annually.
If we talk about neighbours of the USA, the AI engineer in Canada earns anywhere between CAD 90,000 to CAD 130,000 and for Australia, this number stands between AUD 100,000 to AUD 140,000 annually. In the United Kingdom, the average salary of an AI engineer ranges between £50,000 and £80,000 per year.
In India, the AI industry is also growing rapidly. Here, the average salary of an entry-level AI engineer ranges from ₹8 to ₹15 lakhs per year. On the other hand, the top AI professionals easily earn over ₹25 lakhs annually. Now, one thing to remember is that these figures are not fixed. The salary highly ranges depending upon the experience, education, and the industry you work in. However, one thing that is sure that the AI industry is financially rewarding.
So this was the complete information about how to become AI engineer. We hope you got all the information that you need. It is an exciting journey that requires a combination of technical skills and practical experience in order to be successful.
