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Featured Jobs
Artificial Intelligence (AI) Knowledge Curator
The Greater Manchester (GM) AI, Data and Innovation Office (ADIO) Find out more about the daily tasks, overall responsibilities, and required experience for this opportunity by scrolling down now. 1 Year FTC GM has two of the top-five AI ready cities in the UK[1]. We have an opportunity to improve public services and grow the tech economy in Greater Manchester...
Greater Manchester Combined Authority
Manchester
Artificial Intelligence (AI) Knowledge Curator
Job Description The Greater Manchester (GM) AI, Data and Innovation Office (ADIO)1 Year FTCGM has two of the top-five AI ready cities in the UK[1]. We have an opportunity to improve public services and grow the tech economy in Greater Manchester by investing in the way we use AI. To support this ambition, GM has established the ADIO, which acts...
Greater Manchester Combined Authority
Warrington
Artificial Intelligence (AI) Knowledge Curator
Job Description The Greater Manchester (GM) AI, Data and Innovation Office (ADIO)1 Year FTCGM has two of the top-five AI ready cities in the UK[1]. We have an opportunity to improve public services and grow the tech economy in Greater Manchester by investing in the way we use AI. To support this ambition, GM has established the ADIO, which acts...
Greater Manchester Combined Authority
Bolton
Artificial Intelligence Consultant
AI Partner | London (Hybrid) | £80,000 - £95,000 We’re working with a digital delivery business that connects organisations with high-quality near- and offshore development teams. As AI becomes core to modern software delivery, they’re hiring an AI Partner with a strong software engineering background to shape how AI capability is assessed, embedded, and scaled across their partner network. This...
Peaple Talent
London
Artificial Intelligence Consultant
AI Partner | London (Hybrid) | £80,000 - £95,000 We’re working with a digital delivery business that connects organisations with high-quality near- and offshore development teams. As AI becomes core to modern software delivery, they’re hiring an AI Partner with a strong software engineering background to shape how AI capability is assessed, embedded, and scaled across their partner network. This...
Artificial Intelligence / Machine Learning Engineer Technology Incubation & Innovation Lab Location: Staines-upon-Thames, Surrey, UK Working model: Hybrid 3 days onsite, 2 days remote Fixterm 12 month Contract About Our Client Our client is a global technology leader with a dedicated innovation and incubation lab focused on transforming early stage research into real world, scalable products. The lab works on...
If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day.
The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics:
Linear algebra essentials
Probability & statistics for uncertainty & evaluation
Calculus essentials for gradients & backprop
Optimisation basics for training & tuning
A small amount of discrete maths for practical reasoning
This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.
The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia.
If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus.
This guide is written for AI job seekers in the UK. We’ll explore:
What neurodiversity means in an AI context
How ADHD, autism & dyslexia strengths match specific AI roles
Practical workplace adjustments you can ask for under UK law
How to talk about your neurodivergence during applications & interviews
By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.
As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation.
Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead.
This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.
Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production.
This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.
Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles.
Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.
Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design.
This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features.
Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.
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