These days, you can hardly read the news without seeing some headline about new advancements in AI.

It’s not just a field of the future anymore: Artificial Intelligence is having a major impact on the world right now, and the opportunities are only growing. 

All these new developments make AI careers some of the most exciting roles to explore in tech right now. If you’re curious about exactly how to work in artificial intelligence, there are several different artificial intelligence Career paths that can get you there.

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Want to work in artificial intelligence? Check out these 10 potential AI careers!
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This post will introduce you to the main career paths and roles in AI, the skills and education needed, the industries and companies that are hiring, to help you figure out if a career in AI is right for you.

A Quick Introduction to AI Fields

AI, or artificial intelligence, refers to the simulation of human intelligence in machines—they are programmed to think and learn like humans.

Some of the earliest research fields in AI were about creating machines that could perform specific tasks such as playing chess or solving mathematical equations.

Then it became about recreating the decision-making abilities of a human expert.

Today, AI is being used in a wide range of fields, including computer vision, natural language processing, robotics, and healthcare.

Examples of specific AI applications include self-driving cars, personal assistants such as Siri and Alexa, and image and speech recognition systems.

Industry outlook for artificial intelligence careers

By 2030, AI will lead to an estimated $15.7 trillion, or 26% increase, in global GDP, based on PwC’s Global Artificial Intelligence Study. The BLS predicts a broad employment increase of 15% across computer and IT careers in the next decade, which means hundreds of thousands of new tech jobs will become available.

Beyond growing demand and future career stability, careers in AI typically offer lucrative salaries.

Here’s a peek at average salaries for some of the top careers in AI:

1. Deep learning engineer: $160,000
2. Algorithm developer: $159,000
3. Machine learning engineer: $155,000
4. Senior data scientist: $150,000
5. Computer vision engineer: $126,000

When you consider that the average annual salary for someone with a bachelor’s degree in the U.S. is about $52,000 a year, this is an enormous difference.

Transitioning into one of these lucrative AI careers could more than double your salary.

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10 Top Artificial Intelligence Career Paths

What careers are there in AI? Since artificial intelligence is such a huge and varied field, there are a lot of different AI careers, plus jobs where you can use AI skills.

The closest thing to “pure” artificial intelligence jobs are artificial intelligence engineers or machine learning engineers.

What do artificial intelligence career paths typically look like? Usually, you’ll start in a related tech role and work your way into AI jobs.

Some professionals may start as data analysts and then move into more specialized roles like data scientist or machine learning engineer, while others may start as software engineers and then move into AI careers from there. 

Below, we’ll be looking at ten of the top careers in AI, but there are many other roles and sub-specializations within these areas. Depending on the company or industry, there can also be different artificial intelligence job titles for similar or overlapping roles.

1. Data scientist

Average salary: $103,307

Data science is the process of extracting insights and knowledge from structured and unstructured data using statistical, mathematical, and computational methods. This data is typically used to make business decisions.

In the context of AI careers, data science involves gathering, cleaning, and processing data to create algorithms and models that can be used to train AI systems.

Data scientists use a combination of statistical and machine learning techniques to build predictive models, uncover patterns and insights in data, and develop recommendations for business decisions.

Learn more:

• What Is Data Science? How to Learn Data Science and Why It’s Important
• 18 of the Best Data Science Programs & Books
• How to Become a Data Scientist Without a Degree With Fernando Hidalgo
• Learning Data Science as a Beginner With Alice Zhao
• Can I Become a Data Scientist Without a Background In Math?
• How to Teach Yourself Data Science With David Venturi
• Growing a Freelancing Business as a Data Scientist with Lillian Pierson
• Python for Data Science: A Beginner’s Guide

2. AI data analyst

Average salary: $66,752

A data analyst who specializes in AI will generally use artificial intelligence technologies and techniques to analyze data and gain insights.

Data analyst is a more junior role compared to data scientist. Unlike an AI data scientist, they are not generally involved in building AI models or algorithms.

The role of an AI data analyst involves collecting and analyzing large amounts of data from various sources, such as social media, customer feedback, sales data, and other relevant information.

They also use data visualization tools to create reports and dashboards that help decision-makers understand what the data is saying.

Learn more:

• What Is Data Analysis? And How Can You Start Learning It Today
• How to Get Started in Data Analytics With Ben Collins

3. Machine learning engineer

Average salary: $108,563

A machine learning engineer is responsible for designing, developing, and deploying machine learning models and algorithms.

You could say they work at the intersection of software engineering, data science, and computer science, with a focus on building scalable, efficient, and reliable ML systems.

Often, they work with data scientists to develop and improve machine learning models, and they also ensure that models are scalable and can be deployed in a production environment.

Learn more:

• What Is Machine Learning? The Field of the Future
• Career Snapshot: Machine Learning Engineer Jobs, Salary, Skills, & More
• The 13 Best Machine Learning Courses

4. Artificial intelligence engineer

Average salary: $101,773

An artificial intelligence engineer is a professional who designs, builds, and deploys AI systems.

Their main responsibility is to create intelligent systems that can perform tasks that normally require human intelligence, such as understanding natural language, recognizing objects in images, and making predictions based on data.

AI engineering jobs generally include a lot of work with algorithms and models. They research and develop new techniques to build and train AI models, evaluate their performance, and maintain and optimize them.

5. AI research scientist

Average salary: $125,334 

As the name implies, AI research scientists are more involved in the theory side of things than production. An AI research scientist is responsible for conducting research in the field of AI, publishing research papers, and experimenting with algorithms. 

They work on the cutting edge of AI research, and their work often lays the foundation for future developments in the field. Their main responsibility is to push the boundaries of AI technology by designing and implementing innovative solutions to complex problems.

6. Natural language processing engineer

Average salary: $86,485

Natural language processing (or NLP) is a subfield of artificial intelligence that focuses on the interaction between computers and human language.

An NLP engineer is responsible for developing and implementing relevant algorithms and models, such as text-to-speech and speech-to-text systems.

They work with large datasets of text and speech data, collecting and processing it for use in NLP algorithms. They train NLP models on the prepared data using techniques such as supervised learning, unsupervised learning, and reinforcement learning.

7. Computer vision engineer

Average salary: $111,483 

Computer vision engineering is centered around enabling machines to interpret and understand visual data from the real world, such as images and videos. 

In these AI careers, computer vision engineers design, build, and deploy systems that can perform tasks such as object detection and recognition, facial recognition, image and video classification, and scene reconstruction.

They work with large visual datasets and use that information to train and optimize their models.

8. Robotics engineer

Average salary: $85,745

A robotics engineer is responsible for building robots and automation systems. They use a combination of mechanical, electrical, and computer engineering skills to create robots that can perform a wide range of tasks, such as manufacturing, transportation, and healthcare.

Often, these robotic systems incorporate AI technologies, which makes this a potential artificial intelligence career path.

Don’t worry—AI robotics engineers aren’t trying to make the robots take over! They mainly train them to be capable of things like object recognition, path planning, decision-making, etc.

Learn more:

• Building a Robotics Career and the Impact of Mentorship with Camille Eddy

9. Software engineer

Average salary: $90,506 for software engineers and $106,602 for AI software engineers

In this role, you might start out as a general software engineer, then decide to specialize in AI.

Software engineers who pursue jobs in AI programming will generally design and develop software systems that incorporate AI technologies (such as machine learning, natural language processing, and computer vision).

Learn more: 

• What Does a Software Engineer Do?
• 17 Steps to Becoming a Software Engineer (Without a CS Degree)
• Becoming a Software Engineer and Crushing Coder Stereotypes with Laura Medalia

10. AI consultant

Average salary: $101,638

An AI consultant specializes in providing advice and guidance to organizations on how to use AI to achieve their goals. They help companies to identify use cases for AI, create roadmaps for AI adoption, and implement AI solutions.

They often have a background in AI, data science, or consulting, and they work closely with data scientists, engineers, and business leaders to help organizations to leverage AI.

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Skills Needed for AI Careers

Although artificial intelligence careers can vary so widely, there are several skills that most jobs in AI share in common.

If you’re planning to pursue one of these artificial intelligence career paths, here are five categories of skills to start honing.

Disclosure: I’m a proud affiliate for some of the resources mentioned in this article. If you buy a product through my links on this page, I may get a small commission for referring you. Thanks!

1. Mathematics and statistics

A strong background in mathematics and statistics is essential for many roles in AI, including data science and machine learning. You should brush up on topics like calculus, linear algebra, probability, and statistics.

Introductory course:

• Complete Math, Probability & Statistics for Machine Learning (Udemy)

More in-depth course:

• Mathematics for Machine Learning Specialization (Coursera)

2. Programming

Proficiency in languages like Python, R, Java, and C++ is essential for most careers in artificial intelligence. You should also have a solid understanding of computer science concepts like data structures, algorithms, and software development best practices.

Introductory courses: 

• Machine Learning, Data Science and Deep Learning with Python (Udemy)
• R Programming For Absolute Beginners (Udemy)
• Learn Java: Introduction (Codecademy)
• Learn C++: Introduction (Codecademy)

More in-depth courses: 

• AI Programming with Python (Udacity)
• R Programming (DataCamp skill track)
• Learn Java (Codecademy)
• Beginning C++ Programming – From Beginner to Beyond (Udemy)

3. Machine learning

Familiarity with machine learning concepts and techniques—such as supervised and unsupervised learning, deep learning, and reinforcement learning—is necessary for many AI careers. 

Introductory course: 

• Understanding Machine Learning (Pluralsight)

More in-depth course:

• Machine Learning for All (Coursera)

4. Data science

Most AI jobs involve data in some shape or form, since that’s how you train algorithms and models. You should have a good foundation of knowledge about data science concepts and techniques, such as data cleaning, data visualization, and data analysis.

Introductory course:

• Understanding Data Science (DataCamp)

More in-depth course:

• Data Scientist with Python (DataCamp career track)

5. Career-specific skills

If you know what specific artificial intelligence career path you’d like to pursue, make sure you’re preparing yourself with the specific skills required for those AI jobs. 

For instance, if you want to work in natural language processing, it will help to have specific technical skills as well as an understanding of linguistics and language syntax.

If you want to work in computer vision AI engineering, it will help to have experience with image processing techniques and technologies.

One great tip to figure out which skills you need for particular AI careers: look up job listings in the AI fields you’re interested in. This way, you can see what skills and technologies real employers are looking for.

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What Education/Training Do You Need for AI Careers? 

There are many tech careers that are completely accessible without a degree. You can even self-teach your way to becoming a software engineer. 

With AI careers, it’s a bit more challenging. You will likely find it helpful to have a degree in a field related to AI, such as computer science, mathematics, statistics, engineering, or physics.

If you want to get a degree, consider an online degree so you can conveniently fit it into your life.

That said, it’s not always a requirement for AI jobs, and many professionals in the field come from diverse backgrounds—so don’t rule yourself out. 

In AI fields, if you don’t have a degree, you’ll probably need to have a decent amount of experience under your belt.

Maybe you start as a data analyst, transition into data science, then specialize in AI from there. Or teach yourself software engineering with the goal of training for AI engineering jobs once you have experience.

You can learn a lot about the industry through serious online bootcamps and certificate programs like these: 

• AI & Machine Learning Bootcamp (Simplilearn)
• IBM Applied AI Professional Certificate (Coursera)
• AI Programming with Python Nanodegree (Udacity)

If you’re serious about a career in artificial intelligence—whether you have a degree or not—start developing your skills, getting experience, building a portfolio, getting certifications, and making connections.

The sooner you start, the better positioned you’ll be to work in artificial intelligence.

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What Kinds of Industries & Companies Use AI Engineering?

According to a report by Accenture, the industries that are currently leading in AI adoption are technology, automotive, aerospace, and defense. 

Whether you’re interested in AI jobs at large, established companies or startups on the cutting edge of the industry, you’ve got options. Tons of big tech companies have gotten into the AI game, including Google, Facebook, Amazon, Microsoft, IBM, and Apple.

Furthermore, there are thousands of AI startups in the mix. In 2021, AI and machine learning startups collected $115 billion in venture capital funding—an 87% increase from the previous year. 

Contemplating a move to a new city along with that new artificial intelligence career? Some of the best cities for careers in AI include NYC, San Francisco, and San Jose.

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Are AI Careers Right for You?

Because it takes so much time and training to prepare for careers in AI, it’s important for you to be confident that it’s the right move for you. 

An AI career might be a good fit for you if:

• You’re willing to spend time working your way up
• You enjoy problem-solving
• You have good analytical and math skills
• You’re creative and curious
• You don’t mind keeping up with new developments + technologies—fields in AI are rapidly evolving every day

The best way to see if AI jobs excite you in practice as well as in theory is to start getting a little experience.

Take a free or introductory online course to get a feel for how to work in artificial intelligence and what you like (or don’t like) about it. This should also give you an idea of which AI careers might appeal to you most.

Maybe in a few years, you’ll be one of the AI engineers at the forefront of the next big discovery!

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From robotics engineer to data analyst, these AI careers are up and coming!
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