9 Artificial Intelligence (AI) Jobs to Consider in 2025

The outlook is bright for artificial intelligence jobs, which is good news for anyone interested in the growing field of AI. In fact, machine learning engineers and data scientists have been on Indeed’s Best Jobs list for years [1, 2, 3]. Additionally, the US Bureau of Labor Statistics (BLS) projects opportunities in computer and information research to grow 26 percent between 2023 and 2033 [4].

As the prevalence of AI has risen due to generative AI tools like ChatGPT, you may be wondering what jobs are available in this field and how to land one. The following article provides an overview of artificial intelligence careers, and the skills and education you’ll need to pursue them.

9 artificial intelligence jobs to consider

With this list, you can learn more about specific jobs in AI and the average salaries you can expect to earn. You might also consider checking out the following video wherein AI pioneer Andrew Ng outlines key roles for AI upskilling and integration:

1. Artificial intelligence (AI) engineer

AI engineers are professionals who use AI and machine learning techniques to develop applications and systems that help organizations become more efficient. They focus on developing the tools, systems, and processes that enable AI to be applied to real-world problems. Data " trains " algorithms, helping them learn and perform better. AI engineers can help cut costs, increase productivity and profits, and make business recommendations. 

Average base salary: $114,420 [5]

Read more: What Is an AI Engineer? (And How to Become One)

2. Machine learning engineer

Machine learning engineers are professionals who research, build, and design the AI responsible for machine learning. They maintain and improve existing AI systems. A machine learning engineer often serves as a liaison with other data science team members, collaborating with the data scientists who develop models for building AI systems. They run experiments and tests, perform statistical analyses, and develop machine learning systems.

Average base salary: $119,668 [6]

Read more: What Is a Machine Learning Engineer? (+ How to Get Started)

3. Data engineer

Data engineers build systems that collect, manage, and convert raw data into usable information for data scientists, business analysts, and other data professionals to interpret. They make data accessible so that organizations can use it to evaluate and optimize their performance. Data engineering is a broad field with applications in nearly every industry. 

Average base salary: $104,992 [7]

Read more: What Is a Data Engineer?: A Guide to This In-Demand Career

4. Robotics engineer

Robotics engineers develop robotic applications for many industries, including automotive, manufacturing, defense, and medicine. They design new products or assemble prototypes for testing. Some may work on-site at a manufacturing plant overseeing robots as they are being produced, while others monitor their performance in the real world. Robotics engineering combines elements of mechanical and electrical engineering with computer science.

Average base salary: $107,324 [8]

Read more: Guide to a Robotics Engineering Career

5. Software engineer

Software engineers, sometimes called developers, create software for computers and applications. They use programming languages, platforms, and architectures to develop anything from a computer game to network control systems. A software engineer may also test, improve, and maintain software built by other engineers. If you’re an analytical thinker who enjoys solving problems and improving digital systems, you may find this career rewarding.

Average base salary: $111,978 [9]

Read more: Software Engineer Career Path: Overview, Jobs, and Pay

6. Data scientist

Data scientists determine what questions an organization or team should be asking, and help them figure out how to answer those questions using data. They often develop predictive models used to theorize and forecast patterns and outcomes. A data scientist might also use machine learning techniques to improve the quality of data or product offerings. 

Average base salary: $113,913 [10]

Read more: What Is a Data Scientist? Salary, Skills, and How to Become One

7. Natural language processing engineer

Natural language processing (NLP) engineers design natural language processing systems through AI technology to add speech recognition to software and devices, such as office assistants like Alexa or Google Home. They also work with text analytics for sentiment analysis and with language translation.

Average base salary: $88,593 [11]

8. AI research scientist

AI research scientists research, analyze, and develop new models, systems, and algorithms to support AI advancements. They often work in an academic setting, such as a university or research center, and take a theoretical approach. In addition to working on research and development, they're usually tasked with publishing papers and collaborating with other professionals, such as data scientists and engineers.

Average base salary: $142,325 [12]

9. Computer vision engineer

Computer vision engineers are experts in using computer vision to solve problems. Generally, they use AI technology to help computers and systems extract information from visuals and support technology such as facial recognition and image enhancement.

Average base salary: $115,479 [13]

Read more: Essential Computer Vision Skills

How to get a job in AI

When it comes to landing an AI job, you’ll want to consider the requirements and skills associated with a specific job role. These are the common ways to get a job in AI, but keep in mind that your path will vary depending on job type, level, and industry.

1. Consider earning a degree.

Many jobs in AI require a bachelor’s degree or higher. For some entry-level positions, you may only need an associate degree or equivalent skills and work experience. Often, AI professionals obtain undergraduate degrees in computer science, mathematics, or a related field. 

Read more: What Can You Do with a Computer Science Degree? 10 In-Demand Fields

2. Build practical AI skills.

If you already have your undergraduate degree in a field related to AI, consider enrolling in courses to learn the technical skills needed to excel in the field. Even if you don’t have a degree, certifications demonstrate to potential employers that you’re serious about your career goals and investing in your skills. Some AI certifications and certificate programs to consider include:

• MIT: Artificial Intelligence: Implications for Business Strategy

• USAII:  

  • Certified Artificial Intelligence Engineer

  • Certified Artificial Intelligence Consultant

  • Certified Artificial Intelligence Scientist

• ARTIBA: Artificial Intelligence Engineer

• IBM Applied AI Professional Certificate

• IBM AI Engineering Professional Certificate

• Google Advanced Data Analytics Professional Certificate

3. Apply to entry-level jobs.

Once you feel confident with your level of training, start doing research and applying for jobs. Many entry-level AI jobs, such as software engineer or developer, will indicate “entry-level” or “junior” in the job description. Those that require less than three years of experience are typically fair game. 

If you have trouble in your job search, try applying for internships or get started on a freelance project or a hackathon to sharpen your skills. You’ll receive feedback on your work and develop relationships that may benefit you in the future.

Read more: 5 Tech Entry-Level Jobs: No Experience or Commute Required

Prepare for a career in AI with Coursera today

AI is a rapidly growing and changing field. Learn the skills you need to stay up with the field with these courses on Coursera:

For an overview of AI, try the Google's AI Essentials course. This beginner-friendly course is designed to help people across roles and industries gain essential AI skills to boost their productivity on the job.

To prepare for a career in AI engineering, enroll in the Microsoft AI & ML Engineering Professional Certificate. Here, you'll learn to design and implement AI and machine learning infrastructure, master machine learning algorithms, and create AI-powered agents capable of resolving issues autonomously.

If you're planning on earning a degree, consider pursuing a Bachelor of Science in Computer Science from the University of London or even a Master of Science in Data Science from the University of Colorado Boulder.