Generative AI Engineer

IC Resources
Oxford
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist – GenAI & AI Engineering

AI Engineer / Machine Learning Engineer

Machine Learning Engineer III

Machine Learning Engineer II

Machine Learning Engineer II

Senior Lead Analyst - Data Science_ AI/ML & Gen AI

Generative AI Engineer

Oxford, UK (hybrid)

IC Resources is seeking a Generative AI Engineer to join our client's innovative and fast-paced team. This is an exciting opportunity for a skilled AI professional to contribute to cutting-edge natural language processing and machine learning projects. The successful candidate will leverage their expertise in large language models (LLMs) to design, develop, and deploy impactful AI solutions that push technological boundaries.

Primary Responsibilities:

  • Develop advanced AI algorithms tailored to core product requirements.
  • Deploy AI solutions into secure offline environments, ensuring performance and scalability.
  • Collaborate with the wider AI team to integrate novel language models and data enhancement techniques.
  • Stay informed about the latest developments in LLMs and NLP research to maintain a competitive edge.

Essential Experience:

  • Ability to gain UK security clearance*
  • 3+ years of industry experience related to:
  • Deploying LLMs in search pipelines, knowledge of LLMs design, and their applications in production.
  • Expertise in developing and deploying machine learning pipelines, particularly in NLP.
  • Proficiency in Python for machine learning and experience with Docker for system deployment.

Desired Experience:

  • Background in full-stack development, AWS/cloud infrastructure.
  • Experience with Agile product development and MLOps best practices.
  • Familiarity with building RESTful services and data engineering.

What’s On Offer:

  • £DOE
  • Share options
  • Flexible working hours with hybrid working

How to Apply:

If you are an experienced Generative AI Engineer looking to shape the future of AI technology, apply now for immediate consideration. Contact Chris Wyatt, Principal Recruitment Consultant, for more details about this exciting opportunity.

*Please note you must be a UK citizen to gain the security clearance required

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many AI Tools Do You Need to Know to Get an AI Job?

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.

Jobs

What Hiring Managers Look for First in AI Job Applications (UK Guide)

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.

Education

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.