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.

Principal Accountabilities:

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

Essential Criteria:

Qualifications:
- A Master's degree in Artificial Intelligence, Computer Vision, Computer Science, Software Engineering, or a closely related discipline.

Experience:
- Experience of translating business or operational requirements into technical solutions.
- Experience of working with complex or multi-modal datasets, including spatial, temporal, 3D, LiDAR, point cloud, BIM, or sensor data.
- Experience of data engineering and pipeline development, including Extract, Transform, and Load processes.
- Experience in computer vision and visual AI, including classification, detection, segmentation, or anomaly identification tasks.
- Experience of developing and validating machine learning models, including performance evaluation using structured datasets and/or SQL-based systems.
- Experience of designing and delivering end-to-end AI, analytics, and Digital Twin solutions, including deployment and integration with user-facing applications (e.g., dashboards).

Skills, Knowledge & Abilities:
- Strong programming skills in Python for data engineering and machine learning, with familiarity in computer vision frameworks (e.g., OpenCV, PyTorch, TensorFlow, or similar).
- Sound understanding of machine learning workflows, including model design, development, validation, and performance evaluation.
- Understanding of computer vision workflows, including classification, detection, segmentation, or related recognition tasks.
- Ability to design and implement scalable analytical or AI-based solutions for real-world environments.
- Be conversant with version control (e.g., Git) and writing reproducible, well-documented code.
- Understanding of data pipelines, cloud-based systems, or distributed data processing environments.
- Familiarity with data visualisation and dashboard tools for communicating insights.
- Experience handling large, complex, or multi-modal datasets in operational settings.
- Excellent written and verbal communication skills, with the ability to present complex ideas to both technical and non-technical audiences.
- Ability to work independently and collaboratively within multidisciplinary teams.
- Strong organisational skills with the ability to prioritise tasks and meet deadlines.
- Results-driven problem-solving ability with a pragmatic and solution-oriented approach.

Business Requirements:
- This is an office-based role requiring a consistent and visible presence within the office to support effective communication, collaboration, and project delivery.
- Travel to client offices, project sites, and other business locations may be required in line with operational needs.
- Willingness to work flexibly and respond to project needs and stakeholder expectations.
- Willingness to travel between project sites across the UK and Ireland (if required).

Desirable Criteria:

Experience:
- Experience of Digital Twin or simulation-based systems.
- Experience of optimisation, simulation, or scenario-based modelling approaches.
- Experience deploying AI or analytics solutions in cloud or production environments (e.g., AWS, Azure, or similar).
- Experience of applying computer vision techniques in real-world or industrial scenarios.
- Experience of working with engineering or spatial datasets, such as BIM, LiDAR, point-cloud, or 3D data.
- Experience of working with annotated visual datasets for computer vision tasks in infrastructure, inspection, or engineering contexts.

Skills, Knowledge and Abilities:
- Working knowledge of AI system architecture and deployment, including model lifecycle, monitoring, or MLOps practices.
- Understanding of data governance, regulatory requirements (e.g., GDPR), and operational best practices.
- Ability to consider scalability, performance optimisation, reliability, and maintainability in applied AI systems.
- Working knowledge of BIM, LiDAR, or 3D/spatial data workflows.
- Ability to integrate AI outputs into dashboards, business intelligence tools, or decision-support systems.

Benefits:
In addition to a competitive salary, you will have a dedicated budget of £4,000 for further training and career development. You will receive ongoing support from a Supervisor at Saith Ltd, an Academic Supervisor and Academic Lead from the University of Derby. Access to the same training opportunities and facilities as University staff is also provided. Whilst employed by the University of Derby, your terms and conditions will be those of Saith Ltd.