Part of our series What does a ___ actually do?, plain-English guides to the careers students ask us about most.
An AI engineer, often called a machine learning engineer, builds software that learns from data instead of following rules someone wrote by hand. A hospital might want a tool that flags scans worth a second look. A bank might want to catch fraudulent payments, and a factory might want a robot arm that gets faster with practice. The AI engineer works out whether machine learning can solve the problem, builds and tests the model, and gets it running reliably inside a real product.
What the job involves
Talking to a business or research team to understand the problem they want solved.
Collecting and preparing the data a model will learn from.
Developing machine learning models and algorithms, often in Python.
Testing prototypes and analysing the results to improve them.
Finding and fixing bugs.
Assessing the risks of a new model, such as errors or unfair results for some groups of people.
Working with a team to put the model into a live product, then keeping up with new developments in AI.
A typical day
Picture an engineer on a fraud team at a bank. In the morning they check how last night’s model performed: it caught more fraud than the old one, but it also blocked a few hundred genuine customers. Before lunch they dig into those cases and find the model was confused by people paying in a new currency for the first time. In the afternoon they retrain it with extra examples, run the test suite, and present the trade-off to the risk team: how much fraud to catch against how many good customers it is acceptable to annoy.
Much of the work happens in code and in conversations about the results. Every computer and information research scientist who answered the US occupational survey uses email daily, and 69% have face-to-face discussions every day.
Where they work
AI engineers work in technology companies, banks, hospitals, airlines, logistics firms, government and research labs. You could work in an office, at a client’s business or remotely. In the UK, typical hours are 37 to 40 a week.
Is it a good fit for you?
The work is Investigative (asking questions and testing ideas) and Conventional (careful, systematic work with data and code). It could suit you if:
You are strong at maths, especially algebra, statistics and probability.
You have written code, even small projects, and enjoyed debugging them.
You like experiments: try something, measure it, change one thing, try again.
You care whether technology treats people fairly.
Useful languages include Python, SQL and JavaScript.
How to become an AI engineer
Route | What it involves |
|---|---|
University degree | Artificial intelligence, computer science, software engineering, data science or mathematics |
Postgraduate study | Some employers look for a master’s in a related subject such as machine learning, and research-heavy roles often ask for more |
Apprenticeship (UK) | Options include the Machine Learning Engineer Level 6 apprenticeship and the Artificial Intelligence Data Specialist Level 7. These take around 2 years. |
In the UK, a degree usually needs 2 to 3 A levels or equivalent. Maths is the subject that matters most. Further maths and computer science help if your school offers them.
Where to study in the GCC
Undergraduate AI degrees are fairly new in the region. Details are from each university’s official page.
University | Programme | What the university states |
|---|---|---|
BS in Artificial Intelligence | 4 years | |
Hamad Bin Khalifa University, Qatar | BS in Artificial Intelligence and Data Engineering | 4 years, 128 credit hours |
Khalifa University, Abu Dhabi | BSc in Robotics and Artificial Intelligence | 130 credits |
Khalifa University, Abu Dhabi | BSc in Computer Science, AI concentration | 15 credit hours of AI courses within the degree |
KAUST, Saudi Arabia | Master’s and PhD in Computer Science (AI track) | Graduate-only university; an option after your first degree |
Top universities worldwide
Looking beyond the Gulf? These are the top eight for data science and artificial intelligence in the QS World University Rankings by Subject 2026.
Rank | University | Country |
|---|---|---|
1 | Massachusetts Institute of Technology (MIT) | United States |
2 | Stanford University | United States |
3 | National University of Singapore (NUS) | Singapore |
4 | Nanyang Technological University, Singapore (NTU Singapore) | Singapore |
5 | Carnegie Mellon University | United States |
=6 | University of California, Berkeley | United States |
=6 | University of Oxford | United Kingdom |
8 | Harvard University | United States |
At most of these, AI is taught inside computer science or engineering, so a first degree in either is the usual starting point. Rankings mostly reflect research reputation, so read them alongside the course details.
What AI engineers earn
No country’s official statistics have a separate category for AI or machine learning engineers, so these figures use the closest groups, converted to US dollars and rounded:
Country | Closest official group | Lower end | Upper end |
|---|---|---|---|
United States | Computer and information research scientists | $82,000 | $231,000 |
United Kingdom | Programmers and software development professionals | $43,000 | $136,000 |
Canada | Data scientists | $44,000 | $102,000 |
The figures run from the 10th to the 90th percentile of earners in each group. No GCC government publishes pay by job title, so we don’t show regional figures.
Try it now
Try a virtual internship. A Learning Lab’s AI and Computer Science Virtual Internship covers coding, Python and machine learning through real technology projects.
Join a bootcamp in person. A Learning Lab runs an AI Innovation and Leadership Bootcamp in several Gulf cities.
Train your first model. Free beginner tutorials walk you through teaching a computer to recognise handwritten digits in an afternoon. Then try it on data you collected yourself.
Frequently asked questions
What is the difference between an AI engineer and a data scientist?
A data scientist mainly analyses data to answer questions and inform decisions. An AI engineer builds models into software that runs every day, and has to make it fast, reliable and safe at scale. Many people move between the two roles.
How much maths do I need?
A lot, at university level: linear algebra, calculus, probability and statistics. At school, take maths at the highest level you can.
Will AI replace AI engineers?
AI tools already write some of the routine code. The parts that are hardest to automate are deciding what problem to solve, judging whether a model is good enough, and taking responsibility when it goes wrong, and those are a big part of the job.
Not sure if AI is the right path? The HawkNest career assessment matches your interests and strengths to careers like this one.
More in this series
Sources: National Careers Service, Artificial intelligence (AI) engineer; O*NET OnLine, Computer and Information Research Scientists; Skills England, Machine learning engineer; pay from US BLS (May 2025), UK ONS ASHE (2025) and Canada Job Bank (2025), converted at ECB rates of 1 October 2026.
