AI/ Machine Learning Engineer NLP / LLM – Contract

NLP PEOPLE
Salford
1 month ago
Applications closed

Related Jobs

View all jobs

Machine Learning Research Engineer - NLP / LLM

Senior Machine Learning Engineer – Computer Vision

Senior Data Scientist

Machine Learning Engineer

Senior Machine Learning Research Engineer

AI Engineer Machine Learning LLM - Polish Speaking

AI/ Machine Learning Engineer (NLP / LLM) – Contract


Duration: 6 months | Rate: Up to £500 per day | IR35: Outside | Location: Fully Remote (occasional ad-hoc travel to office)


A leading Regulatory Tech company is seeking a Contract Machine Learning Engineer / Data Scientist to support the development of next-generation AI solutions. This is an exciting opportunity to play a key role in designing and training Large Language Models (LLMs) from the ground up, and to contribute to the creation of an intelligent AI‑powered chatbot that transforms the way information and insights are delivered. You’ll work closely with the client’s in‑house data and engineering teams to design, train, and fine‑tune transformer‑based models for complex natural language processing tasks, ensuring accuracy, efficiency, and scalability.


Experience Requirements

  • Proven experience in Natural Language Processing (NLP) and Large Language Models (LLMs), including training LLMs from scratch.
  • Strong understanding of deep learning principles and experience working with transformer‑based architectures (e.g., GPT, BERT, T5).
  • Solid background in data science and machine learning, including model development, training, evaluation, and deployment.
  • Experience building and deploying chatbots or conversational AI systems.
  • Knowledge of MLOps tools and pipelines for model versioning and deployment.

If you are available and interested in a 6-month Outside IR35 contract, please apply in the first instance and you will be contacted to discuss the position further.


Company

Involved Solutions


Qualifications

  • Senior (5+ years of experience)


#J-18808-Ljbffr

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.

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.

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.

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.