KTP Associate in AI-Powered Predictive MaintenanceUniversity

Location:  Genie UK, The Maltings, Wharf Road, Grantham, Lincolnshire, NG31 6BH (hybrid)

Contract Type:  Fixed Term (36 months)

Basis:  Full Time

Interview Date:  Monday 26 October 2026

About this role:

This Knowledge Transfer Partnership, between Aston University and Genie UK Limited, offers an opportunity to oversee the development of an advanced AI-driven predictive and prescriptive maintenance system for Genies lifting equipment. The project focuses on connected, partially connected, and non-connected machines, transforming telematics, onboard sensor data, and historical maintenance data into actionable maintenance intelligence within Genies LiftConnect platform. You will contribute to a sector-leading project, with responsibilities that include developing intelligent data-quality agents, predictive models that can transfer across machine families, prescriptive decision support, operational dashboards, and ensuring the delivery of methodologies, documentation, training, and workshops needed to integrate the solution into the business.

Essential:

Demonstrable experience in software tools for data analysis, such as SQL, Power BI, and cloud-based analytics environments

Feature extraction and time-series analysis

Probabilistic prediction techniques using scalable Python-based development environments such as PyTorch or TensorFlow

Cloud-native machine learning and MLOps environments such as AWS SageMaker

Small or large language model development with retrieval-augmented generation

Desirable:

Industrial analytics or predictive maintenance

Knowledge of construction-related industries and market drivers

Commercial awareness to connect technical development with business impact, budget awareness, and resource management

£40,000 to £42,000 depending on experience plus £2000 per annum personal development budget