The IT industry is one of the most rapidly growing industries in the world. By 2026, its market volume is expected to reach a sensational $1.5 trillion.
At the same time, Artificial Intelligence (AI) is gaining momentum as well. This innovative technology was expected to make $22.6 billion in 2020, according to Statista.
Therefore, it seems that both of these industries are very attractive for tech masterminds. But the question is, how to get there?
In this post, I am breaking down the path to an AI career into separate phases to learn what it takes to become a successful Artificial Intelligence engineer.
What Is Artificial Intelligence?
The technology of artificial intelligence is innovative and controversial. Because it is very powerful—while at the same time still not well explored—people are afraid of it, and start telling stories of AI taking over the world and replacing humans as workers.
Now, what I am certain about is that AI sprang from machine learning technology. Instead of training machines all the time, engineers created a combination of algorithms so the machines could train themselves.
And bingo! We’ve got the technology for the 21st century.
In years, the algorithms became so proficient that they now engage in what we call “deep learning.” They need less and less human input, and are becoming much more autonomous. Besides, AI has at its disposal much more information now than it ever did, which creates even more opportunities to learn.
AI technology finds application in almost any industry: healthcare, transportation, finance, VR gaming, advertising, manufacturing, and many more.
What Does Cloud Storage Have to Do With AI?
For a couple of years, we have been witnessing massive cloud migration. In other words because of affordability, environmental issues, and cybersecurity, businesses are relocating online services from physical servers to cloud storage.
Why is AI relevant here? Because AI powers cloud servers and is able to learn from the data it stores. In such a way it can solve the problems before anyone even notices, or even predict and prevent problems from ever happening.
Amazon’s Alexa and the Google Assistant are great examples of how wondrous merging between cloud and AI can be. Also, these features only announce the upcoming megatrend of similar devices we can expect in the future.
In turn, this trend creates a huge demand for AI engineers that will maintain AI-powered cloud systems.
Where Can I Work in AI?
All that being said, the next question is “Where can you work as an AI expert?” Here are some industries, companies, and even government agencies that are currently thriving from AI.
Technology and Computer Science
Quality assurance (QA) testing is a crucial service for software development. The QA market is expected to reach $49.9 Billion by 2026, which is more than twice the worth it has today. So, knowing how to employ AI and machine learning (ML) for software testing and debugging could be a profitable skill.
Another example would be Facebook or, as they prefer to call it nowadays, Meta. It is a well-known social media platform that developed Oculus virtual reality using AI.
- Open vacancies: At the moment, there are 100+ AI-related vacancies at Meta, and these include Research Scientist, Optical Scientist, SWE specialist, and many more.
- All experience levels are welcome, from interns to specialists.
- Usually, a Bachelor’s degree in AI engineering is the minimum requirement.
- In most cases, at least 1+ years of professional experience is required
- Over 80% of all AI engineers in the world work at either Facebook or Google.
Moreover, don’t forget that Facebook/Meta also owns one of the most popular messaging apps, Whatsapp. Whatsapp for business created a chatbot so that people can communicate with businesses as if talking to a real person. For example, the people behind an eCommerce site can train the chatbot to provide information about the current delivery status of something that has been ordered.
As previously mentioned, Amazon is the creator of Alexa, an interactive AI system. In September 2021, the company announced that it planned to hire 55,000 people for corporate and technology roles.
- Open vacancies: At the moment, there are 800+ AI-related vacancies at Amazon, including Data Scientist, Applied Scientist, Software Development Engineer, Deep Learning Architect, and many more.
- Both remote and in-office jobs are available.
- Usually, at least 2+ years of professional experience are required
- In general, at least a Bachelor's degree in computer science is required.
Healthcare is where AI technology is most promising. In 2019 alone, investors poured more than $4B into healthcare AI startups. After the pandemic, the interest in healthcare improvements will only continue to grow.
A basic Google search reveals hundreds of jobs related to AI and healthcare, such as Learning Specialist, Principal Architect, Senior Healthcare IT Consultant, and more.
AI systems help food production by improving the overall quality and profitability of harvest. In 2020, the percent of AI job posts in the agricultural sector doubled.
The most common agritech job posts are:
- Software Engineer
- UI/UX Specialist
- Data Analyst
- AI Specialist
- Business Development and Sales
- Digital Content Creator
- Marketing Communications
- Finance (Operations and Corporate Finance).
AI algorithms help scientists at NASA understand huge amounts of data about the universe. Currently, there are more than 150+ AI-related vacancies at NASA Jet Propulsion Laboratory, including Data Scientist, Senior Software Engineer, Software Systems Engineer, and more.
There are a lot of startups that develop apps to help marketers automatize their strategies. And, as you might guess, most of them are looking for AI engineers.
SMS marketing strategies can largely benefit from AI. For example, an AI-powered SMS API can execute SMS marketing campaigns quickly and efficiently. Beyond that, AI can help with content creation, generic or frequent questions, and many elements of personalized customer experience.
Still, don’t forget that although companies on this list are the world’s most successful companies, they are not the only ones applying AI. On the contrary, AI is becoming a major trend and more businesses are implementing it as we speak.
Not all of them are large-scale, so, while there currently are a lot of job opportunities in AI, you may need to know where to look and how to present yourself.
Technical Skills Required in AI
In order to become an AI expert, there is a complex set of skills an individual needs to have. To begin with technical skills, here is what an average AI and ML engineer is expected to know:
- R, Python, Java, C++
- Quantitative analysis
- Business acumen
- Hadoop, Spark
- Probability and statistics calculations
- Reporting and presentation skills
- Database administration
- Data analysis
- Data visualization
- Extraction and signal processing techniques
- Unix tools (awk, grep, cat, sort, find, cut, tr, etc.)
Of course, depending on the seniority level and the particular job post, you might not need to know all of the things on this list. For example, to apply for the entry-level Research Intern post at Facebook, you would need:
- Ph.D. or Masters in computer science or related field
- Published papers in the domain of computer science or related field
- To know how to work in C, C++, Python, Lua, or other
- Quantitative analytical skills
- Experience in deep learning
- Experience in data analytics
On the other hand, to work as a Senior Software Development Engineer at Amazon you would need:
- 2+ years of experience contributing to the architecture and design of new and current systems.
- 3+ years of programming experience with Java, C++, or C#.
- 4+ years of professional software development experience.
- 2+ years of experience as a mentor, tech lead OR leading an engineering team.
- Experience with deep learning systems.
As you can see, each job post is special, but you can expect that entry-level positions will put emphasis on what you are familiar with, while senior-level positions will value what you can actually do.
Other than having knowledge of the aforementioned software and tools, an AI expert is expected to be:
- up-to-date with the latest trends
- a quick learner
As an aspiring AI engineer, you should pay attention to your soft skills for several reasons. First of all, for most of the job positions listed above, you will most probably not work in a vacuum. You will be a part of a team, and you will need to navigate your way through a complex social and corporate system.
Secondly, while AI is about programming and computers, its purpose is to understand, adapt to, and imitate real human behavior. Therefore, in order to make AI systems that are useful to customers, you have to understand human needs and psychology.
In general, companies consider a master’s degree in computer science a minimum for hiring for an AI post. Of course, higher-level education comes as a plus.
Besides, the particular type of computer science degree is also relevant. A general course in computer science can only briefly touch upon AI. On the other hand, a specialized degree in AI is much more valuable for the employer.
Another important element for employers is your portfolio. If you have strong previous experience in programming, then they might disregard a lack of a postgraduate degree. Simply, employers value experience much more than theoretical knowledge.
Additionally, there are a variety of alternative ways to learn about AI. There are development courses and bootcamps, webinars, online courses, and so on. You can either start like that or complement your general knowledge in computer science.
Once you get your degree, you’re up against at least fifty other people who also have a degree. How do you distinguish yourself from them? The answer is, of course, experience.
Remember that it is crucial to think about your portfolio even before you get your degree.
One of the ways to gain distinctive experience in AI is to become a member of AI-focused communities at your university. You can participate in exciting personal or school projects, or do an internship.
Of course, you will see that some opportunities are better than others and more valued by future employers. Try to look out for courses and internships at acclaimed companies.
For example, let’s say you are choosing between free AI courses offered by your university and the $200 professional machine-learning engineer certification by Google. Unless the course provided by your university is something really special, you probably want to invest in Google’s training. It will sound much better in the ears of your future employer.
For most employers, a working experience of at least one year is extremely important. It shows them that you have at least a basic understanding of how things work in practice. Also, it helps them determine how relevant you are for the particular job post.
Locating a Job in AI
Finally, once you have your diploma, an exciting portfolio, and a burning desire to have an excellent career, you will start looking for your first job.
The most important places to look for a job are LinkedIn, ZipRecruiter, and Google Job Search. These platforms are the most popular and connect you with the greatest number of employers. As you’re looking for the ideal job, consider the career path you hope to take, as technology jobs have many different directions.
The other way to do it is to approach a company directly. The choice of a company might depend on your personal interests and previous knowledge. For example, if you have some interest in language and linguistics but still want to work as an AI expert, then you can approach companies such as Grammarly or Jarvis.
Alternatively, you could join the explosion of AI that’s taking over web development. You would work at any of the companies that will be established to meet rising need over the next couple of years, in addition to existing giants such as Amazon and Google.
Finally, a number of professional organizations and public institutions in your country might require AI specialists.
A Career in Artificial Intelligence and Salary
One thing is certain: AI engineers are among the best-paid experts in the world. The average annual income for AI-related positions in the US was $126,830/year in 2020. And, in 2022, it grew to $137,750. Most AI engineers start with $112,355/year while senior-level positions make up to $195,000 annually.
On the other hand, machine learning is paid a bit less, around $112,930 annually. However, the forecasts say that the demand for ML is growing and that engineers will soon earn as much as AI experts.
Now You're Ready for a Rewarding AI Career
Working as an AI specialist is a very promising career. However, as usually is the case, starting can be tough at first.
In order to stand out in the AI labor market, you need to provide a specific mix of formal education, working experience, and personal skills.
Artificial Intelligence is here to stay. It finds application in a wide set of activities, from web development to healthcare and gaming. That is good news because it means that the demand for AI experts will only continue to grow in the future.