AI engineer

What does an AI engineer do?

• Design, train and test machine learning models for specific tasks.
• Prepare large data sets and build pipelines that feed data into models.
• Build applications on top of existing AI models, for example chatbots or search tools.
• Deploy models into products and make sure they run quickly and reliably.
• Monitor models after launch and retrain them when data or performance changes.
• Check models for errors, bias, security risks and possible misuse.
• Work with data scientists, software developers and product teams to agree goals.

Where do they work?

AI engineers work for technology companies, start-ups, banks, retailers, healthcare and pharmaceutical firms, car makers, consultancies, universities and government research agencies. Large organisations may have separate research and product teams. In smaller firms, AI engineers often do a mix of data work, model building and software development. The work is computer-based, and hybrid and remote work is common. Pressure can be high when products depend on new AI features.

What skills do you need?

• Programming in Python
• Machine learning and deep learning
• Linear algebra, probability and statistics
• Software engineering and testing
• Data pipelines and cloud computing
• Evaluating model quality and bias
• Problem solving
• Keeping up with fast-changing research

Official skills profile (ESCO)

Essential skills listed for this occupation in ESCO, the European Commission's multilingual classification of skills and occupations.

• apply ICT systems theory
• manage ICT semantic integration
• use markup languages
• design database scheme
• develop creative ideas
• design application interfaces
• manage database
• analyse business requirements
• assess ICT knowledge
• define technical requirements
• design process

Essential knowledge: resource description framework query language · ICT security legislation · systems development life-cycle · business process modelling · principles of artificial intelligence · natural language processing · systems theory · database development tools

How do you become an AI engineer?

Most AI engineers have a bachelor's degree in computer science, mathematics, data science, physics or electrical engineering, and many also have a master's degree in machine learning or artificial intelligence. Research roles often require a PhD. You need strong programming and software engineering skills as well as the mathematics behind machine learning. A common path is to work first as a software developer or data scientist and then specialise. Projects that show you can train, evaluate and deploy a model, or build a useful AI application, carry a lot of weight with employers.

1. University degree. A bachelor's degree in computer science, mathematics, data science or engineering, followed by a master's degree in artificial intelligence or machine learning, is the most common route. Final-year projects, research assistant work and internships in AI teams help you stand out from other graduates.
2. PhD and research. A PhD in machine learning, computer vision, natural language processing or a related field leads to research scientist and advanced engineering roles in universities and industry labs. It usually takes three to six years, depending on the country, and published research strengthens your applications.
3. Switching from software or data work. Many AI engineers start as software developers, data engineers or data scientists. They learn machine learning through online courses, internal projects and open-source tools, then move into AI teams. Strong engineering skills are highly valued, because much AI work involves making models reliable in real products.

Degrees that lead to this career

• Computer science

  A computer science degree teaches how software, data and computer systems work, from programming and algorithms to networks and artificial intelligence.

  9 linked careers

• Data science

  A data science degree teaches how to collect, clean, analyse and learn from data, combining statistics, programming and machine learning with knowledge of real-world problems.

  6 linked careers

• Mathematics

  A mathematics degree develops advanced reasoning and problem-solving through pure mathematics, such as algebra and analysis, and applied areas, such as statistics, modelling and computing.

  6 linked careers

• Physics

  A physics degree explores the laws that govern the universe, from particles and atoms to materials, energy and stars, using mathematics, experiments and computer models.

  6 linked careers

• Electrical engineering

  An electrical engineering degree teaches how to design and build systems that generate, control and use electricity, from power grids and motors to circuits, chips and communication networks.

  5 linked careers

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Do you need a licence to work as an AI engineer?

AI engineering is not a licensed profession, and no specific qualification is legally required. However, governments are introducing rules for AI systems. Some regions, including the European Union, now place duties on organisations that build or use AI in high-risk areas such as hiring, credit or healthcare. Data protection and copyright laws also affect how training data can be used. The rules are changing quickly and differ between countries.

How much does an AI engineer earn?

The US Bureau of Labor Statistics does not publish a separate pay estimate that matches this occupation, so we do not show one.

Earnings of Professionals around the world

Most countries do not publish pay for single job titles. The International Labour Organization collects median monthly earnings for broad occupation groups instead. This career belongs to ISCO-08 major group 2, "Professionals". The table covers the whole group, which includes AI engineer and many other occupations.

Source: ILOSTAT, median monthly earnings of employees, latest year available. PPP$ adjusts for price differences between countries so figures can be compared. "vs all employees" compares the group's median with the median for all occupations in the same country.

Career progression

1. Junior machine learning engineer
2. AI or machine learning engineer
3. Senior AI engineer
4. Staff or principal AI engineer
5. Head of AI or machine learning

Job outlook

Demand for AI skills has grown quickly as organisations try to use machine learning and generative AI in their products and operations. The field changes very fast, so tools and methods you learn today may be replaced within a few years. Some tasks, such as building simple AI applications, are becoming easier with ready-made models and services. Engineers who understand the fundamentals, evaluate systems carefully and deal with safety, cost and reliability are likely to stay in demand.

Questions about becoming an AI engineer

What is the difference between an AI engineer and a data scientist?

Data scientists focus on analysing data and building models to answer questions or support decisions. AI or machine learning engineers focus on turning models into reliable software that runs in real products at scale. The roles overlap, and in smaller organisations one person may do both.

Do you need a PhD to become an AI engineer?

No, most AI engineering jobs do not require a PhD. A bachelor's or master's degree in a relevant subject plus strong software skills is usually enough for product-focused roles. A PhD is often expected for research scientist jobs that develop new methods rather than apply existing ones.

How much maths do you need for machine learning?

You need a solid working knowledge of linear algebra, calculus, probability and statistics to understand how models learn and why they fail. Many engineering roles use ready-made libraries, so you rarely do the calculations by hand, but research roles require much deeper mathematics.

Can a software developer become an AI engineer?

Yes, this is one of the most common routes. Developers already have the programming and engineering skills that AI teams need. To switch, learn the maths and core machine learning methods, build projects that use real data, and look for chances to work on AI features in your current job.

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Sources

1. ILOSTAT — Median monthly earnings of employees by occupation — ISCO-08 major groups, latest year per country
2. European Commission — ESCO occupation profile — ESCO code 2511.10

How to cite this page: CourseToJob (2026). How to become an AI engineer: degrees, skills and salary. https://coursetojob.com/careers/ai-engineer/ (accessed September 26, 2026)

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