GenAi / LLM Engineer (SC Clearance)

IC Resources
Oxford
11 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Research Engineer

Senior Data Scientist with a GenAI focus

Data Scientist (Full Stack)

Job Title:Generative AI/LLM Engineer (Contract)

Contract Type:6-Month Contract (Outside IR35) /Active SC Clearance is essential 

About the Role:
We are looking for a highly skilledGenerative AI/LLM Engineerfor a 6-month contract to deliver cutting-edge AI solutions. The role focuses on designing, implementing, and optimising large language model (LLM) applications, with a particular emphasis onRetrieval-Augmented Generation (RAG)workflows. Experience withgraph networksand/ortopic modelingis highly desirable to enhance reasoning and thematic understanding.

Key Responsibilities:

  • Design and develop generative AI solutions using LLMs, incorporating RAG techniques for efficient retrieval and generation workflows.
  • Leverage graph networks and topic modeling to enhance structured reasoning and thematic contextualisation in AI systems.
  • Collaborate with cross-functional teams to deploy scalable AI solutions tailored to project requirements.
  • Optimise LLM performance through fine-tuning, data preprocessing, and custom model architecture design.

Key Requirements:

  • Proven experience in building and deploying applications with LLMs and generative AI techniques.
  • Strong understanding of Retrieval-Augmented Generation (RAG).
  • Hands-on expertise with graph networks and/or topic modeling techniques.
  • Proficiency in Python and machine learning frameworks (e.g., PyTorch, TensorFlow).
  • ActiveSC Clearance(mandatory for consideration).
  • Excellent problem-solving skills and the ability to work autonomously within a fast-paced environment.

This is a unique opportunity to work on high-impact projects, leveraging your expertise in generative AI and LLMs within a secure and innovative environment. Please apply now if interested.

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.

Education

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

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

Careers Jobs

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

🍪 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.