KTP Associate in AI-Powered Predictive Maintenance

Aston University; Birmingham; Hybrid; GBP 40,000 - 42,000; Full time

Benefits offered by this job

Personal development budget

Job summary

A Knowledge Transfer Partnership between Aston University and Genie UK Limited offers a role to oversee the development of an AI-driven predictive and prescriptive maintenance system for Genies lifting equipment within Genies LiftConnect platform.

Responsibilities include building data-quality agents, predictive models transferable across machine families, prescriptive decision support, and operational dashboards, plus delivering methodologies, documentation, training and workshops to integrate

Qualifications

• Experience with data analysis tools such as SQL and Power BI.
• Feature extraction and time-series analysis.
• Probabilistic prediction using Python-based environments such as PyTorch or TensorFlow.
• Cloud-native ML and MLOps environments (AWS SageMaker).
• Language model development and retrieval-augmented generation.

Responsibilities

• Develop intelligent data-quality agents and predictive models transferable across machine families.
• Create prescriptive decision support and operational dashboards.
• Ensure delivery of methodologies, documentation, training and workshops for integration into the business.

Skills

Data analysis

Time-series analysis

LLM development

Retrieval augmented generation

Tools

SQL

Power BI

Python

PyTorch

TensorFlow

AWS SageMaker

Job description

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