9 Artificial Intelligence Jobs to Explore in 2026

Key takeaways

As the use of artificial intelligence continues to grow, so too will AI jobs. That’s good news for anyone interested in joining the growing field of AI-focused roles

• AI jobs are routinely ranked highly in the job market. In fact, machine learning engineers and data scientists have been on Indeed’s Best Jobs list for years [1]

• Positions in the field are growing. According to the US Bureau of Labor Statistics (BLS) projects opportunities in computer and information research to grow 20 percent between 2024 and 2034 [2]

• Example job titles in this field include AI engineer, ML engineer, data engineer, and data scientist

Learn more about AI jobs, including what they do and how much you can expect to earn in each. Afterward, if you’re ready to build a strong foundation in AI, consider enrolling in the Google AI Professional Certificate program. In as little as eight hours, you’ll learn to apply AI to essential, transferable skills like data analysis, communication, and research

9 artificial intelligence jobs to explore

Artificial intelligence professionals are increasingly in demand and well-compensated for their hard-earned skills. If you’re interested in joining the field, consider pursuing one of these positions:

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. 

Median total pay:$151,000 [3]

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.

Medina total pay:$160,000 [4]

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. 

Median total pay:$132,000 [5]

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.

Median total pay:$143,000 [6]

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.

Median total pay:$149,000 [7]

6. Data scientist

Data scientistsdetermine 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. 

Median total pay:$155,000 [8]

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

Median total pay: $112,000 [9]

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.

Median total pay: $196,000 [10]

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

Median total pay:$164,000 [11]

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. 

2. Build practical AI skills

To join the AI field, you’ll need to build the right skills. Programming skills, for example, are essential for any AI worker. In addition to Python, you may also use C++, Java, and R frequently. You’ll also need to have extensive knowledge of ML frameworks such as PyTorch and TensorFlow, as well as a variety of ML and deep learning algorithms

Because AI interfaces are vulnerable to cyberattacks, it’s also beneficial to have knowledge of AI security measures. If your company plans to release a new AI model for general use, you’ll need to know about DevOps deployment techniques to ensure your AI model is usable in a general way

AI career paths

If you’re a team member interested in pursuing AI as a career path, you can start defining your trajectory by using AI on your team. Then, decide what function or role you’d like to play in AI

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 will indicate “entry-level” or “junior” in the job title or require less than three years of experience

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

<img src="https://justfineinfotech.com/wp-content/uploads/2026/07/Why_-CAREER-_Needs_to_Understand_AI_-_Project_Management__4_.jpg" alt="[Video thumbnail] AI Revolution From Coffee to Cybersecurity“>

Prepare for a career in AI with Coursera today

AI is a rapidly growing and changing field. Stay updated on the latest trends with our LinkedIn newsletter, Career Chat! Or, browse our other free re

• Watch on YouTube:IBM AI Experts Reveal Prompt Engineering Secrets

• Explore courses:Popular Artificial Intelligence Courses and Certifications

Accelerate your career growth with a Coursera Plus subscription. When you enroll in either the monthly or annual option, you’ll get access to over 10,000 courses. 

Build job-ready skills with Coursera Plus

Start 7-day free trial
Start 7-day free trial

Article sources

1. 

Indeed. “The Best Jobs in the US in 2019, https://www.indeed.com/lead/best-jobs-2019.” Accessed April 20, 2026

Updated on Apr 20, 2026
Written by:

Coursera Staff

Editorial Team

Coursera’s editorial team is comprised of highly experienced professional editors, writers, and fact

This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals

Source: www.coursera.org