How to get a job in AI

Artificial intelligence (AI) is a rapidly growing field that is transforming industries worldwide. From designing advanced models to ensuring the ethical use of technology, a career in AI is an opportunity to shape the future

What jobs can I do in AI?

A career in AI goes far beyond coding. There are roles for a wide range of skills and interests, meaning graduates from diverse backgrounds - including the arts - can find their niche. Areas you could explore include:

AI adoption - guide organisations in implementing AI and transforming their operations.
Engineering - apply AI to solve real-world problems with practical solutions.
Product development - design and manage AI-powered tools that deliver measurable impact.
Policy and ethics - advise on fairness, privacy, and societal implications to ensure responsible AI.
Research - explore how machines learn, reason, and make decisions.

Common job roles include:

To explore more options, see our IT job profiles.

What AI companies can I work for?

AI isn't limited to tech giants. Today, it's embedded across almost every sector:

AI-focused companies - firms like DeepMind and OpenAI develop AI as their core product.
Industry roles using AI - apply AI in fields like finance, healthcare, or marketing to solve practical, real-world problems.

You'll find opportunities to work with AI in areas such as:

For example, in health informatics, AI can improve diagnostics, optimise treatments, and streamline hospital operations. Tasks may include:

managing patient flow
predicting disease risks
suggesting personalised treatment plans.

Explore our job sectors to see how AI is shaping the job market.

Do I need a degree to work in AI?

Not always. While degrees help, strong technical and analytical skills matter most. Here are some of the top educational paths to kickstart a career in AI.

Bachelors degrees

You'll have the best chance of landing an AI role if you have a background in areas that many recruiters value, such as:

Discover big data courses.

Some roles, especially in AI ethics, natural language processing (NLP), or human-centred AI, also welcome degrees in:

Masters degrees

Postgraduate study, such as an MSc in AI or machine learning, can give you a competitive edge, especially if you're aiming for research-focused roles. These programmes often provide exposure to:

complex algorithms
hands-on projects
large datasets.

Search postgraduate courses in artificial intelligence.

Apprenticeships

Combining learning with practical experience, AI apprenticeships range from Level 3 (A-level equivalent) to Level 7 (Masters equivalent) and often lead to full-time roles.

For instance, the AI Champion Apprenticeship at Decoded offers 13 months of hands-on training using Microsoft and OpenAI tools. Skills gained include:

AI-driven data analysis
document automation
prompt engineering
responsible AI practices.

For a degree-level option, the AI Engineer Level 6 Apprenticeship at BPP covers the full AI lifecycle, including:

computer vision
generative AI
machine learning
neural networks
NLP.

Delivered by industry experts, it combines technical training with soft skills and optional certifications.

Read our essential guide to apprenticeships.

Skills bootcamps

If you're changing careers or retraining in AI, skills bootcamps offer practical training for free, supported by industry partners.

For example, the Level 5 AI and Machine Learning Bootcamp with Gateshead Council prepares you for roles such as AI engineer or data scientist. Through blended learning, you'll build skills in:

data processing
model development with TensorFlow and PyTorch
Python.

For beginners, Functional Skills UK's Practical AI in the Workplace bootcamp is a 12-week course that focuses on areas in education or business. It helps you apply AI effectively in real-world settings.

To apply for skills bootcamps, you'll usually need to:

be aged 19 or over
have lived in England for the past three years
not be enrolled in another government-funded course.

Requirements can vary by region, so be sure to check the criteria in your area before applying.

Online learning

You don't need a formal qualification to start building AI skills. Online courses allow you to learn at your own pace, strengthen your coding skills, and create projects you can showcase to employers.

If you're figuring out whether AI is a good fit for you, consider:

If you already have some experience and want to level up, explore:

Search for short AI courses.

What skills do I need for AI jobs?

AI roles need more than just coding - they require a mix of specialist and interpersonal skills.

Technical skills:

Programming tools - familiarity with Python, R, Java, or C++, and know your way around Jupyter Notebooks, VS Code, Anaconda, and Git/GitHub to build, test, and deploy AI systems.
Maths and statistics - linear algebra, probability, and statistics form the backbone of AI to understand models, handle uncertainty, and evaluate performance reliably.
Data handling - you'll need to clean, transform, and explore data using tools like Pandas, NumPy, and SQL.

Soft skills:

communication
ethical reasoning
project management
teamwork.

Discover what skills employers want.

How can I get AI experience?

Breaking into AI can feel daunting, but there are lots of ways to gain work experience while building your skills and network.

Competitions and hackathons

Participating in these fast-paced events helps you solve real problems, gain practical experience, and expand your network. Focusing on niche areas like NLP, computer vision, or AI ethics can give you a competitive advantage.

Some options include:

AI hackathons hosted on platforms like Devpost or HackMIT
the Google AI Student Challenge
Kaggle competitions with beginner-friendly datasets
the Microsoft Imagine Cup in the AI or ML category.

Graduate schemes

Allowing you to rotate across teams and projects, providing real-world experience with cutting-edge AI, graduate schemes offer mentoring and the potential for a full-time role at the end of the programme.

For example, the Data Science and AI Graduate Programme at AstraZeneca offers two years of global placements, where you could work on:

AI-driven molecule design
optimising clinical trials
predictive toxicity modelling.

If finding an AI-specific graduate scheme is challenging, many broader graduate programmes include AI-focused pathways.

For instance, Capgemini's Analytics and AI (A&AI) entry route within their Accelerate programme is designed for graduates passionate about data science. It focuses on developing both technical and consulting skills and has two stages:

The Institute (three months) - build core consulting skills and gain broad business insight.
Analytics and AI Academy (18 months) - work on client projects, transformations, and internal initiatives.

Search for artificial intelligence graduate schemes.

Internships

Work on live AI projects while receiving mentorship from experienced professionals through an internship.

Leading employer, J.P.鈥疢organ鈥疌hase, offers two AI internship pathways:

AI Research Programme - collaborate with global researchers on foundational AI advancements, including cryptography and machine learning.
Machine Learning Centre of Excellence Internship - deploy scalable AI solutions in finance and operations, working with NLP, speech recognition, time series, and reinforcement learning.

For more information or to apply, visit JPMorganChase & Co - AI Opportunities.

For PhD students, the Turing Internship Network connects researchers with leading organisations across the UK and Ireland for full or part-time roles in data science and AI. With three recruitment rounds each year, past partners include:

Department for Transport (DfT)
Environmental Investigation Agency (EIA)
HSBC
Ministry of Defence (MoD).

To explore more opportunities, search for artificial intelligence internships.

Work placements

Immersing yourself in industry practices, work placements provide hands-on experience and exposure to ethical AI considerations and emerging trends.

For example, Google's AI Student Researcher Programme provides 12 to 24-week placements for undergraduate, postgraduate, and PhD students. You'll work alongside some of the world's leading AI experts, joining teams such as DeepMind or Google Research, contributing to new research and socially impactful projects while aligning tasks with your skills and interests.

For younger students aged 15 to 18, Study Mind's Coding and AI Work Experience offers one- or two-week placements to develop practical skills in coding, AI, and problem-solving. You'll:

learn Python
explore machine learning
tackle real-world AI projects
visit a tech company to see AI specialists in action.

The programme also covers AI ethics and career insights, helping you build teamwork and creativity, while providing a solid foundation for university applications in AI or computer science.

Where can I find AI graduate jobs?

If you're just starting out in AI, you'll find no shortage of paths to explore.

Leading tech companies are constantly on the lookout for AI engineers, researchers, and data scientists to drive the next wave of innovation. Some of the biggest employers include:

Beyond the tech giants, there are also specialist AI organisations shaping the future of the field, such as:

Don't overlook the startup scene either. These firms provide the chance to work on new challenges while giving you more responsibility from day one.

Other major UK employers, such as the NHS, are increasingly hiring AI roles to optimise their workforce. These positions often focus on workforce analytics, resource planning, and AI-driven healthcare solutions. You can search for these roles at NHS Jobs.

To discover openings, explore AI and tech-focused job boards:

AIjobsboard.com - a general AI job search.
foorilla - dedicated to AI, machine learning, and data science roles.
Y Combinator's 'Work at a Startup' - many smaller AI firms post here.

If you're drawn to the scientific side of AI, universities and research labs offer opportunities to advance both theory and application. Look at their career portals and lab websites, where they list research assistant, PhD, and postdoc openings. Explore how to get an academic job.

How do I apply for an AI job?

AI is constantly evolving, so your first step is to narrow down the roles that best match your skills and interests.

When you're ready to apply, craft a tailored CV and cover letter that shows you understand the company's work and explains how your skills can add value. See our tips on using AI in job applications.

To make your work stand out, share your projects and link to them in your application:

GitHub - upload projects with clear documentation and READMEs.
Kaggle - Datasets - share datasets and models to build a portfolio.
LinkedIn - showcase certificates and link to your projects to attract recruiters.

You could also consider creating a portfolio website as a central hub with project summaries, blogs, and code samples.

Networking is just as important as your technical skills. By joining AI communities, you can stay up to date, learn from others, and discover job openings that aren't widely advertised.

Popular networks include:

Hugging Face forums
Reddit communities like r/MachineLearning and /r/Artificialintelligence
the Saturdays.AI community.

What can I expect in an AI job interview?

If you're preparing for an interview for an AI job, expect a mix of technical challenges and behavioural questions. You might face:

Algorithm and data structure problems.
Coding challenges in Python or other programming languages.
Machine learning, deep learning, or NLP tasks.
Numerical reasoning tests covering data sets, number series, and statistics.
Psychometric tests that assess communication, teamwork, and problem solving.

Read our guide on acing the SHL interview test.

Some interviews also lean heavily into system design, asking you to map out solutions, weigh alternatives, and explain your reasoning clearly.

To give yourself the best shot, prepare by mixing coding practice with a careful look at your past projects. Make sure you can explain even the trickiest AI concepts in simple, clear language - like you're telling the story of what you built and why it matters.

Practicing mock interviews and revising good questions to ask at an interview can also help you approach them with confidence and be ready to tackle whatever comes your way.

Discover our interview preparation tips.

Find out more

Get the lowdown on how AI is influencing graduate careers.
Discover how to break into AI by listening to the Future You podcast.
Explore what else the information technology sector has to offer.