AI, Computer Vision & Digital Twin Engineer (KTP Associate)

University of Derby’s College of Science and Engineering in partnership with Saith Ltd are offering an exciting career-development opportunity to manage and deliver a challenging strategic Knowledge Transfer Partnership (KTP) project. Based at Saith Ltd’s premises in Hampshire, you will be employed by the University as a KTP Associate but work under the terms and conditions of the company.

You will lead the design, development, and deployment of a practical, production-ready AI-enabled Digital Twin platform to support intelligent asset management within energy and utility infrastructure. You will work at the interface of research and industry, translating advanced AI, computer vision, and data-driven methods into scalable solutions deployed within live engineering environments.

You will take ownership of the end-to-end system lifecycle, integrating multi-source data including BIM, LiDAR, point cloud, and operational datasets to develop solutions for automated inspection, anomaly detection, predictive maintenance, and intelligent decision-support. Crucially, you will ensure that solutions are commercially viable, aligned with client requirements, and deliver measurable operational value.

Working closely with design, construction, and operational teams, you will contribute directly to live engineering projects, ensuring solutions are effectively integrated, validated, and deliver real-world impact. The role will also support the adoption of AI and Digital Twin technologies within Saith through training, knowledge transfer, and integration into operational workflows.

Duties and Responsibilities

Main responsibilities include:

1. Translate stakeholder and operational needs into technical system designs through co-design workshops and engagement with engineers, clients, industry partners, and academics.
2. Ensure solutions align with client requirements and deliver measurable operational and commercial value.
3. Design and maintain data pipelines and infrastructure for ingesting, processing, and managing spatial, temporal, and operational data.
4. Process and integrate BIM, LiDAR, and point-cloud data into consistent and usable Digital Twin environments.
5. Develop and apply machine learning and computer vision models for component recognition, anomaly detection, compliance monitoring, and predictive maintenance.
6. Design and implement an AI-enabled Digital Twin system integrating multi-source data for infrastructure asset management.
7. Work closely with design, construction, and operational teams to integrate and validate solutions in live projects and real-world environments.
8. Develop simulation and risk analysis tools to support inspection, maintenance planning, and operational decision-making.
9. Create dashboards and decision-support tools to visualise data and communicate actionable insights.
10. Lead pilot deployment, system testing, and performance evaluation in real-world environments.
11. Drive adoption of AI and Digital Twin technologies within Saith through training, documentation, and embedding of new workflows across the business.
12. Deliver practical, deployable outputs within the KTP timeframe, prioritising implementation and operational impact.

This is an exciting career-development opportunity to deliver a high-impact project, working with academic experts and industry professionals, and gaining hands-on experience in deploying advanced AI solutions within a real-world engineering consultancy environment.

Using your knowledge and skills to support the business and achieve specific project aims, you will receive on-going support by a Supervisor at Saith Ltd, an Academic Supervisor and Academic Lead from the University of Derby to help you deliver. A personal training and development budget will also be available for you to access, as well as receiving access to the same training opportunities and facilities as University staff.

This is a unique opportunity to contribute to the development of scalable digital solutions, supporting improved asset performance, operational efficiency, and data-driven decision-making across infrastructure and utility sectors. You will also have the opportunity to contribute to the long-term development of AI and Digital Twin capability within the organisation, supporting future growth and innovation.