AI Jobs in the UK: Engineering, Training and Entry-Level Roles, With Pay and How to Get In
A guide to working in AI in the UK, covering technical roles such as AI and machine learning engineer and non-technical routes such as data annotation, model evaluation and AI governance, with pay and entry routes.
By Tony Musso on
AI jobs in the UK fall into two broad groups. Technical roles build and run AI systems: AI engineer, machine learning engineer, MLOps engineer, data scientist, NLP engineer and computer vision engineer. Non-technical and entry-level roles shape, test and roll out AI: data annotator, model evaluator, prompt engineer, implementation specialist, AI trainer, product specialist and governance specialist.
Technical roles pay the most but usually need strong coding and maths. The non-technical side is easier to enter, especially from admin, writing, teaching, operations, compliance or project work. Pay figures below come from TonyKnows career data and are full-time salaries.
AI jobs at a glance
| Role | Starting pay (TonyKnows career data) | Main entry route |
|---|---|---|
| AI engineer | Around £40,000 to £65,000 | Software engineering plus AI projects |
| Machine learning engineer | Around £45,000 to £70,000 | Degree in CS, maths or stats, then ML work |
| MLOps engineer | Around £50,000 to £70,000 | DevOps or cloud engineering |
| Data scientist | Around £35,000 to £50,000 | Stats, maths or CS degree, often a master's or PhD |
| NLP engineer | Around £45,000 to £65,000 | ML engineering with a language focus |
| Computer vision engineer | Around £45,000 to £65,000 | ML engineering with an image and video focus |
| AI data annotator | Around £22,000 to £28,000 | No degree needed, detail and guidelines |
| AI model evaluator | Around £32,000 to £45,000 | Annotation, QA or analysis plus some Python |
| AI prompt engineer | Around £35,000 to £50,000 | Strong writing plus testing and some Python |
| AI trainer | Around £35,000 to £50,000 | Training, teaching or L&D |
| AI implementation specialist | Around £40,000 to £55,000 | Operations, IT or automation |
| AI product specialist | Around £45,000 to £60,000 | Product management or data |
| AI governance specialist | Around £45,000 to £60,000 | Compliance, risk, legal or data protection |
Technical AI jobs
These are the "AI engineering jobs" most people mean. They are mostly hybrid or remote, desk-based and well paid, but competition for first roles is strong.
AI engineer
AI engineers build products and features on top of AI models, connecting them to data, apps and business systems. TonyKnows career data puts pay at around £40,000 to £65,000 to start, £75,000 to £120,000 mid-career and £130,000 to £220,000+ at senior level.
How people get in: most move across from software engineering. A CS or maths degree helps, but a strong portfolio of working AI projects is often accepted. If you are starting from scratch, our guide on how to become a software engineer is the first step.
Machine learning engineer
Machine learning engineers train, tune and deploy models. Pay is around £45,000 to £70,000 to start, £80,000 to £130,000 mid-career and £140,000 to £220,000+ senior.
How people get in: a degree in computer science, maths, statistics or a related subject is usually expected, followed by work as a software engineer or data scientist.
MLOps engineer
MLOps engineers run the pipelines, monitoring and cloud infrastructure that keep models working in production. Pay is around £50,000 to £70,000 to start and £85,000 to £120,000 mid-career.
How people get in: usually from DevOps, cloud or platform engineering. Docker, Kubernetes, CI/CD and a major cloud platform matter more than a degree.
Data scientist
Data scientists use statistics and machine learning to answer business questions and build predictive models. Pay is around £35,000 to £50,000 to start and £60,000 to £95,000 mid-career.
How people get in: a degree in stats, maths or CS is usually required, and many hold a master's or PhD. Others step up from data analyst roles after building strong Python and modelling skills.
NLP engineer and computer vision engineer
NLP engineers work on systems that handle language, such as chatbots, search and document processing. Computer vision engineers work on images and video, in areas such as medical imaging, manufacturing inspection and autonomous systems. Both pay around £45,000 to £65,000 to start and £80,000 to £120,000 mid-career.
How people get in: both are specialisms within ML engineering. A degree helps but is not always required. Focused projects in the area you want to specialise in carry a lot of weight.
Non-technical and entry-level AI jobs
You do not need to be a programmer to work in AI. These roles reward clear thinking, careful writing, domain knowledge and the ability to explain AI to other people.
AI data annotator
AI data annotators label text, images and audio so models can learn from them. Salaried roles pay around £22,000 to £28,000 to start and £30,000 to £40,000 mid-career.
How people get in: no degree needed. Employers test attention to detail, consistency and how well you follow detailed guidelines.
AI model evaluator
AI model evaluators design tests and scoring rubrics to measure how well models perform, and check for errors and bias. Pay is around £32,000 to £45,000 to start and £50,000 to £75,000 mid-career.
How people get in: often a step up from annotation or QA testing. Basic statistics and some Python make a big difference.
AI prompt engineer
AI prompt engineers design and test the instructions and workflows that get reliable results from large language models. Pay is around £35,000 to £50,000 to start and £55,000 to £80,000 mid-career.
How people get in: a portfolio matters more than a degree. Strong writers who learn testing and some Python do well. Many employers fold this work into wider AI engineering or product roles, so look beyond the exact job title.
AI trainer
In job adverts, an AI trainer usually means someone who trains staff to use AI tools well, through workshops, guides and coaching. Pay is around £35,000 to £50,000 to start and £55,000 to £85,000 mid-career.
How people get in: usually from teaching, learning and development, or a team lead role where you were already the person showing colleagues new tools.
AI implementation specialist
AI implementation specialists take AI plans and put them into a company's daily tools and workflows. Pay is around £40,000 to £55,000 to start and £65,000 to £95,000 mid-career.
How people get in: from operations, IT support, business analysis or automation work. Knowing how a business really runs matters as much as knowing the tools.
AI product specialist
AI product specialists are product managers focused on AI features, from idea to testing to launch. Pay is around £45,000 to £60,000 to start and £70,000 to £100,000 mid-career.
How people get in: usually three to five years in product management or data first.
AI governance specialist
AI governance specialists set the rules for how an organisation uses AI safely and legally, covering risk, data protection and policy. UK organisations that sell into the EU may also need to meet the EU AI Act. Pay is around £45,000 to £60,000 to start and £70,000 to £100,000 mid-career.
How people get in: from compliance, risk, legal, audit or data protection roles. Clear policy writing is a core skill.
What "AI training jobs" really involve
Search for AI training jobs and most results are not salaried roles. They are freelance tasks: writing and rating chatbot answers, checking facts, labelling data or solving problems so a model can learn from them. Be clear about what this work is before you rely on it.
- It is usually freelance and platform-based. You sign up, pass screening tests and pick up tasks. You are normally self-employed, so you handle your own tax through Self Assessment.
- Pay and hours are variable. Rates depend on the project and your skills. Work can be plentiful one week and dry up the next, and projects can end without notice.
- Specialists earn more. People with expertise in coding, maths, science, law, medicine or a second language are often offered better-paid tasks than general raters.
- Quality is monitored. Your work is reviewed, and low scores can mean fewer tasks.
- Watch for scams. A genuine platform never asks you to pay to join or to buy training.
Treat it as flexible side income or a way to gain experience, not a stable salary. It can be a real stepping stone, though. Annotation and rating experience is a good base for salaried annotator, evaluator or quality roles.
How to get into AI: a realistic plan
- Pick the side that fits you. If you enjoy coding and maths, aim for engineering. If your strengths are writing, teaching, operations or compliance, aim for the non-technical roles. Career Compass can help you decide.
- Build from where you are. Most people move into AI from a related job rather than starting cold. A developer becomes an AI engineer, a compliance officer moves into governance, a trainer becomes an AI trainer.
- Make evidence. Build small projects, write up evaluations you ran, or lead an AI rollout in your current team. Employers hire on what you have done.
- Use funded training. Free Skills Bootcamps in England include data, software and AI-related courses.
- Rewrite your CV for AI roles. Our CV builder, CV Studio, helps you reframe your experience for the role you want.
This guide is about working in AI. If you want to know how AI might affect your current job, see will AI take my job or our list of AI-proof jobs.
Start with the AI data annotator guide
Frequently asked questions
Can I get an AI job without a degree?
Yes. AI data annotator, prompt engineer, AI trainer and implementation specialist roles often accept people without a degree if they can show the right skills. Even AI engineering roles sometimes accept a strong portfolio instead. Machine learning engineer and data scientist roles usually expect a relevant degree.
Are AI training jobs legitimate?
Many are, but most are freelance tasks on online platforms rather than salaried jobs. Pay and hours vary and projects can end without warning. A genuine platform will never charge you to join, sell you training or ask for payment before you can work.
What is the highest paying AI job in the UK?
Among the roles in this guide, AI engineers, machine learning engineers, NLP engineers and computer vision engineers reach the highest senior pay, at around £130,000 to £220,000+ in TonyKnows career data. Research scientist roles, which usually need a PhD, can pay more again.
What is the easiest AI job to get into?
AI data annotation is usually the easiest entry point. It needs no degree, just accuracy, consistency and the ability to follow detailed guidelines. From there, many people progress into model evaluation or quality roles by adding basic statistics and some Python.
Do I need to learn Python to work in AI?
For engineering, data science and model evaluation, yes. For annotation, AI training, implementation and governance, it helps but is not essential. Clear writing, domain knowledge and an understanding of how AI tools behave in practice often matter more in those roles.