AI Systems Engineer (KTP Associate)

Loughborough University - Department of Computer Science/School of Science/Business School

Nationwide Air Conditioning

Full time, fixed term for 24 months

About the project

This is a 24-month Knowledge Transfer Partnership (KTP) project between Loughborough University and Nationwide Air Conditioning, funded by UKRI Innovate UK.

The project is to develop an AI-powered system that automates the generation of service and project quotes based on defect inputs, and real-time supply chain performance, embedding decision-making algorithms and learning mechanisms into business operations, whilst moving away from manual and repetitive tasks, and toward automation grounded in historical data and real-time inputs. The project will create a market-ready AI product capable of reducing quotation turnaround from days to minutes.

This is an exciting opportunity for a forward-thinking and ambitious specialist in computer vision and machine learning to join a company that specialises in providing HVAC Solutions to Clients. Working with Clients from the biggest retail, hospitality, commercial and leisure sectors in the UK, you will be joining a company that offers 24/7 service, enhancing environments and providing optimal performance.

The KTP will integrate multi-criteria decision-making logic and machine learning models to match defects with suitable solutions and accurately estimate time and cost. The system will incorporate supply chain optimisation algorithms that dynamically evaluate supplier options based on lead time, service performance, transport costs, and delivery reliability.

The KTP Associate can either be based at the NAC Head Office in Agusta House, Commerce Way, Edenbridge, Kent, TN8 6ED or the NAC London office at 224 Shoreditch High St, London, E1 6PJ. There will also be some travel to Loughborough University, spending time with the academic teams in the Department of Computer Science and the Business School. The Associate will be supervised by an academic team, led by Lead Academic Prof Donato Masi and Academic Supervisor Dr George Vogiatzis, who are experts in their academic fields.

For more information refer to the Job Description and Person Specification.

Informal enquiries should be made to the Lead Academic, Donato Masi D.Masi@lboro.ac.uk

Applications

The closing date for receipt of applications: 30th November 2025

Interviews:

There will be a 2-stage interview process.

Stage 1: Monday 8th December

Stage 2: Monday 15th December

Stage 1 will be an online interview, which will take place on Monday 8th December 2025.

Successful candidates will go through to stage 2, which will be on Monday 15th December at NAC Head Office in Edenbridge.

The interview process will include a short assessment of skills required for the role, a presentation and interview questions.