Generative AI Engineer

IC Resources
Oxford
1 year ago
Applications closed

Related Jobs

View all jobs

Senior AI Engineer | GenAI | Information Retrieval | ML | NLP | Hybrid London | Up to £130k

Senior AI Engineer | GenAI | Information Retrieval | ML | NLP | Hybrid London | Up to £130k

ML & AI Engineering Lead: Generative AI & MLOps

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

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 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.

Education Jobs

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

🍪 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.