An AI Engineer designs, develops, and implements artificial intelligence systems and solutions. These professionals use programming languages such as Python and frameworks like TensorFlow or PyTorch to build machine learning models, natural language processing systems, and computer vision applications. AI Engineers often work as part of a team, collaborating with data scientists, software developers, and business analysts to solve complex problems and automate processes. Daily tasks can include data analysis, model training and evaluation, software integration, and keeping up to date with the latest AI research. The role is in high demand in various industries, including finance, healthcare, automotive, and technology.
AI Engineers in the UK typically earn between £45,000 and £80,000 per year, with senior roles exceeding £100,000 in some cases.
There has been an estimated 35 percent increase in AI-related job postings in the UK from 2022 to 2023, reflecting growing demand across sectors.
The UK AI sector employs over 50,000 people and is projected to be worth over £1 trillion to the UK economy by 2035.
Focuses on designing and developing machine learning models and systems that enable computers to learn from data and make decisions.
Specialises in building systems that understand, interpret, and generate human language, such as chatbots or translation tools.
Works on developing algorithms and technologies that enable computers to interpret and understand visual information from the world, such as images and videos.
Take subjects like Maths, Physics, and Computer Science at GCSE and A-level to develop analytical and problem-solving skills.
Strong maths skills, especially in algebra, calculus, and statistics, are essential for understanding algorithms and data analysis in AI. Computer Science will introduce you to programming and basic computational thinking, which are vital for this career.
Start learning coding languages such as Python, Java, or C++ through school, online courses, or coding clubs.
Python is particularly popular in AI due to its simplicity and vast libraries for data science and machine learning. Many free resources and beginner tutorials are available online. Practising early will make university-level coursework easier.
Apply for a university degree in Computer Science, Artificial Intelligence, Data Science, or a closely related field.
Most AI Engineer roles require at least a bachelor's degree. These courses cover algorithms, data structures, software engineering, and often include modules specifically on AI and machine learning. Some universities offer dedicated AI degrees or specialisations.
Study for a master’s or PhD in AI, Machine Learning, or Data Science to deepen your knowledge and research skills.
While not always required, postgraduate qualifications are highly valued for advanced roles. A master’s or doctoral programme allows you to specialise in areas like deep learning, natural language processing, or robotics, and opens doors to research positions.
Work on your own AI projects or contribute to open-source projects to showcase your skills.
Creating projects, such as chatbots, image recognisers, or recommendation systems, helps demonstrate your technical ability to employers. Platforms like GitHub are useful for sharing code and collaborating with others.
Gain practical experience through industry placements, internships, or summer programmes related to AI or data science.
Internships provide exposure to real-world AI applications and can help you build professional contacts. Many tech companies offer structured placements for students and recent graduates.
Look for entry-level positions such as Junior AI Engineer, Machine Learning Engineer, or Data Scientist.
Tailor your CV to highlight relevant projects, skills, and academic achievements. Be prepared to discuss your technical knowledge and demonstrate problem-solving abilities during interviews.
Stay updated on new AI technologies and attend events or join AI communities.
AI is a rapidly evolving field. Continue learning through online courses or professional certifications, and participate in hackathons or conferences to network with other professionals and keep your skills current.
Data Scientists collect, analyse, and interpret large datasets to provide insights and support decision-making, often using machine learning techniques.
Machine Learning Engineers focus specifically on designing and building machine learning models and algorithms for software applications.
Software Developers create, test, and maintain software applications, and may work closely with AI Engineers to integrate AI features into products.
Explore relevant apprenticeships that can help you kickstart your career in AI Engineer. Apprenticeships offer hands-on experience and training while earning a wage.
This page showcases various career options and the pathways to reach them. Each career listed here shares transferable skills and knowledge, making it easier for individuals to transition between them.
Your current career is highlighted to help you see how it fits into the broader landscape of potential career choices. By clicking on any career, you can learn more about it, including the training and education required to pursue it.
Remember, progressing in your career often involves further learning and training. This page provides insights into future career options as well as those that can lead up to your current one.
These career progression decisions are informed by comparing the skills and knowledge needed for different occupations, along with data on how people move between them. Explore the possibilities and discover the exciting journey ahead in your career!
The AI Engineer role most closely aligns with the Artificial Intelligence (AI) engineer career because both focus on developing and implementing AI technologies, algorithms, and models. The qualifications required, such as expertise in machine learning, programming, and data analysis, are similar, making these roles essentially comparable within the field of artificial intelligence.
You can get into this job through:
You could do a degree in a subject like:
Some employers may also look for a postgraduate qualification in a related subject like machine learning.
You could sign up to do a free UCAS Subject Spotlight to learn more about AI and machine learning.
You'll usually need:
You could apply to do an apprenticeship, for example:
These apprenticeships are equivalent to degree and postgraduate level study and take around 2 years to complete.
You'll usually need:
It will be helpful if you have knowledge and experience of computer programming languages, such as Python, SQL or JavaScript.
You might be able to apply to do a Skills Bootcamp in AI or machine learning.
Skills Bootcamps are free, flexible courses that last up to 16 weeks. You should check specific entry requirements with the course provider.
You could join The Society for the Study of Artificial Intelligence and Simulation of Behaviour (AISB) for training opportunities and to make industry contacts.
You can keep up to date with new technological advances and industry information from:
Explore other careers or use our AI to discover personalised paths based on your interests.
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