eWEEK content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More.
A career in in artificial intelligence involves supporting the practice of using AI algorithms to simulate human intelligence, clearly a growing sector. AI continues to dominate the tech industry. Because of AI’s growth, many organizations are striving to quickly hire qualified – or even semi-qualified – experts, so an AI career will offer enormous opportunity for growth.
To be sure, AI is highly complex, and its complexity requires professional expertise to build a successful career. Still, for tech professionals, this is an incredible opportunity to get in on the ground floor of many emerging AI career paths. AI careers tend to have highly competitive salaries, with six figures as a starting point.
In this guide, we discuss the potential outlook for AI careers, as well as 10 career paths to consider for your potential AI career.
Key point: We also discuss how you can start a career in artificial intelligence. See below.
Also see: Generative AI Companies: Top 12 Leaders
AI Careers: Leading Positions
The AI career positions below range from AI consultant to AI programmer to research scientist, but realize that many of these positions may overlap with one another. Indeed, the actual duties of AI careers are shifting as the AI sector itself undergoes rapid growth.
AI Consultant
The AI consultant is currently one of the most sought-after professionals when it comes to artificial intelligence jobs/careers.
AI consultants are responsible for supporting businesses and other organizations in implementing AI. Responsibilities include everything from managing implementation projects to ensuring AI solutions are compatible with an organization’s needs.
Because of these varying duties, AI consultants must understand AI in its entirety. They must understand complex topics such as machine learning and deep learning, as well as how to construct and use algorithms.
AI Prompt Specialist
Also known as prompt engineers, these specialists are tasked with developing prompts to be used with generative AI tools. Some of these tools include ChatGPT and Midjourney.
Prompts guide these AI tools and help them produce specific results. Prompt specialists must understand how these tools work and how best to communicate with them. Because of the wide use of these tools, prompt specialists can work in a wide range of industries, from advertising to manufacturing.
Also see: Generative AI Startups
AI Programmer
A career as an AI programmer requires expertise in using algorithms to program AI-based services, apps and software. These programmers are also responsible for training machines to produce human-like input and for troubleshooting issues within AI-based tools.
Programmers must have a solid handle on programming languages such as Python and Java. They must also understand the basics of software development and know the ins and outs of AI concepts.
AI Developer
While similar to programmers, an AI developer instead develops and designs the AI-based services, apps and software organizations use. For example, AI developers ensure that the user interface of an AI-based tool is easy to use.
AI developers also test software applications to ensure they result in the desired outcomes. In some cases, AI programmers and developers will work alongside one another.
Developers must have solid problem-solving skills and creativity, while also understanding data engineering and analytics. This AI career tends to be highly lucrative.
On a related topic: What is Generative AI?
Data Scientist
A data scientist’s key responsibility is solving complex problems using data. Data scientists perform a wide range of duties, including building models using programming languages, finding patterns in data sets, communicating insights to stakeholders and consulting with organizations on how to best use their data.
Data science plays a key role in AI. Scientists work to build the algorithms necessary to uncover patterns. Those patterns can then be used to train AI models.
Research Scientist
As AI continues to evolve, organizations will need to find innovative ways to use it. An AI career as a research scientists involves researching the use of AI to uncover new opportunities. They also build algorithms and perform experiments to test new AI methods.
Research scientists must be inquisitive and creative. They must also have a firm grasp on complex subjects such as statistics, data analytics, machine learning and natural language processing.
On a related topic: The Future of Artificial Intelligence
Machine Learning Engineer
The machine learning engineer plays a critical role in the development of AI programs, applications and software. Machine learning engineers work to design the models and algorithms that make AI work.
The process of designing these models requires the engineer to organize data, test models, program models using languages like Python and other responsibilities.
Deep Learning Engineer
Deep learning is a branch of machine learning. However, deep learning goes beyond machine learning in that it enables AI models to learn and make their own decisions. In other words, it enables machines to learn and act in the same way the human brain does.
Deep learning engineers use this process to build highly intelligent AI models, most often for the purpose of predictive analytics. These engineers must be experts in machine learning, neural networking, data science and programming.
Learn more: What Is Deep Learning?
NLP Engineer
NLP stands for natural language processing, which refers to a computer’s ability to understand human language. NLP is one force behind popular AI tools such as chatbots like ChatGPT.
A career as an NLP engineers requires deep expertise programming AI models and systems that can understand human language. This means that while NLP engineers must understand programming and AI, they must also be experts in language and linguistics.
Learn more: Top Natural Language Processing Companies 2022
Robotics Engineer
Robotics engineers are tasked with using machines and algorithms to build robots. They’re also responsible for testing and maintaining robotic machines across a wide range of industries, from manufacturing to retail.
The skills required to be a robotics engineer are a unique mix. Not only do you need to understand AI, programming, and mathematics, but you must also have mechanical skills.
How to Start a Career in Artificial Intelligence
If a career in AI seems like a fit for you, there are a few steps you must take to get started, including selecting a career path, obtaining the proper training, and building a portfolio to showcase your experience to potential employers.
Select an AI career path
The first step is to choose an AI career path. This should be based on factors such as your future career goals, current skill set and interests.
For example, while all aspects of AI require the use of math, some careers will be more math-heavy than others. If you’re a numbers person, a career as a data scientist or programmer might be a solid choice for you.
However, if you simply enjoy being on the bleeding edge of technology, you may opt for robotics. As AI is a wide-open field, be sure to do your research to uncover the constantly shifting AI jobs market.
Also see: Generative AI Startups
Obtain the proper education and training
The next step is to obtain the proper education and training for your selected career path. Education will vary, depending on what you choose.
For example, if you wish to start a career as an AI programmer, you’ll need to understand programming languages such as Python, as well as AI-specific concepts like machine learning. On the other hand, an AI consultant will need to understand data science and the ins and outs of AI.
There are various methods for obtaining the required training. For example, you can take various AI-related courses online or opt for a traditional college program. Often, organizations will also offer internship programs where students can learn AI in a real-world environment.
Learn more: Best Machine Learning Platforms 2022
Build your AI portfolio
Building your portfolio will ensure you have proof of your AI-specific skill set. To build a portfolio, complete AI projects that pertain to your chosen career path. For example, build a machine learning model or algorithm, or design a chatbot.
AI Careers: Market Outlook
The artificial intelligence industry is in the middle of a boom. According to recent data, the market size was $95.60 billion in 2021. However, by 2030, the market size is forecasted to reach $1.8 trillion, growing at a stunning CAGR of 32.9%.
This growth will drive AI companies and other organizations to look for additional support. According to the Bureau of Labor Statistics, computer and information technology jobs will increase by 15% between now and 2031. This is much faster than average growth when compared to all other occupations.
Job opportunities range from those specific to AI to those specific to data and machine learning. Due to the nature of AI and its complexities, there are virtually endless career paths to choose from.
For more information, also see: Top AI Startups
The Bottom Line: AI Careers Will Continue to Thrive
As the AI industry continues to grow, so will the opportunities for a highly successful career as an AI professional. While AI requires a machine to do the technical work, humans must still be the masterminds behind it. If you’re considering a new career path in tech, a career in AI might be an exceptionally rewarding fit.
For more information, also see: Top Robotics Startups