Closing Date: 29 March 2026 Salary: £64,490 - £86,255 Location: Cambridge - Triangle/Hybrid (2 days per week in the office) Contract: Permanent Hours: Full Time (35 hours per week) Shape the future of AI-powered learning solutions with Cambridge University Press & Assessment, a world-leading academic publisher and assessment organisation, and a proud part of the University of Cambridge. This is...
Cambridge University Press & Assessment
Cambridge
Senior Machine Learning Research Engineer
Location: Cambridge - Triangle/Hybrid (2 days per week in the office)Contract: PermanentHours: Full Time (35 hours per week)Shape the future of AI-powered learning solutions with Cambridge University Press & Assessment, a world-leading academic publisher and assessment organisation, and a proud part of the University of Cambridge.This is an exciting opportunity for Machine Learning Research Engineers to join our innovative Applied...
Machine Learning Jobs UK
Cambridge
Artificial Intelligence Engineer
OpenText is a global leader in information management, where innovation, creativity, and collaboration are the key components of our corporate culture. As a member of our team, you will have the opportunity to partner with the most highly regarded companies in the world, tackle complex issues, and contribute to projects that shape the future of digital transformation. At OpenText, AI...
Machine Learning Research Engineer - NLP / LLM An incredible opportunity for a Machine Learning Research Engineer to work on researching and investigating new concepts for an industry-leading, machine-learning software company in Cambridge, UK. This unique opportunity is ideally suited to those with a Ph.D. Relating to classic Machine Learning and Natural Language Processing and its application to an ever-advancing...
Jobster
Cambridge
Machine Learning Research Engineer – NLP / LLM
Machine Learning Research Engineer – NLP / LLM An incredible opportunity for a Machine Learning Research Engineer to work on researching and investigating new concepts for an industry-leading, machine-learning software company in Cambridge, UK. This unique opportunity is ideally suited to those with a Ph.D. relating to classic Machine Learning and Natural Language Processing and its application to an ever-advancing...
NLP PEOPLE
Plymouth
Machine Learning Research Engineer – NLP / LLM
OverviewMachine Learning Research Engineer – NLP / LLMAn incredible opportunity for a Machine Learning Research Engineer to work on researching and investigating new concepts for an industry-leading, machine-learning software company in Cambridge, UK. This unique opportunity is ideally suited to those with a Ph.D. relating to classic Machine Learning and Natural Language Processing and its application to an ever-advancing technical...
If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes.
Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes.
So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional.
This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.
Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds.
This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.
Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy.
Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews.
At the heart of this disconnect lies a growing and uncomfortable truth:
Universities are not fully preparing graduates for real-world AI jobs.
This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.
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