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

Overview

This role will be based on site, primarily in the named location, at Saith Ltd's premises in Hampshire. You will be employed by the University of Derby as a KTP Associate but work under the terms and conditions of Saith Ltd.

The University of Derby's College of Science and Engineering in partnership with Saith Ltd is offering a career development opportunity to manage and deliver a challenging strategic Knowledge Transfer Partnership (KTP) project.

Responsibilities

• 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.
• Own 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.
• Ensure solutions are commercially viable, aligned with client requirements, and deliver measurable operational value.
• Contribute directly to live engineering projects, ensuring solutions are effectively integrated, validated, and deliver real world impact.
• Support the adoption of AI and Digital Twin technologies within Saith through training, knowledge transfer, and integration into operational workflows.
• Lead pilot deployment, system testing, and performance evaluation in real world environments.
• Deliver practical, deployable outputs within the KTP timeframe, prioritising implementation and operational impact.

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 fac ing applications (e.g., dashboards).
• 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 & 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.
• Alignment with organisational values and professional conduct standards.

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).

Knowledge Transfer Partnership (KTP)

This full time post is part funded by the UK Government's KTP programme. A KTP is a three way project between a graduate, an organisation and a university. In addition to a competitive salary and core KTP development training, you will have a dedicated budget of £4,000 for further training and career development. Visit: ktp-uk.org/graduates for more information.

Visa Eligibility

The offered salary for this role is less than the going rate for the occupation and the minimum salary threshold for the Skilled Worker route (£41,700 per annum, as of 22nd July 2025). Therefore you will only be eligible to apply for a Skilled Worker visa subject to your individual circumstances which must meet one of the following criteria set out by UKVI:

• Your job is on the Immigration Skills List.
• You're under 26, studying or a recent graduate, or in professional training.
• You have a PhD level qualification that's relevant to your job.
• You have a postdoctoral position in science or higher education.

The University of Derby is committed to promoting equity, diversity and inclusion, regardless of age, disability, trans status, marriage and civil partnership, pregnancy and maternity, race, religion or belief (or none), sex and sexual orientation.

We are Disability Confident Employers, demonstrating our commitment to disability inclusion, and invite applicants to highlight adjustments they may require to ensure equitable participation in our recruitment processes.

We are committed to ensuring an environment which is trans and non binary inclusive for all our staff, students, partners and visitors, and continuously review our policies, guidance and training.

When applying to join the University, you can choose your preferred title, including the gender neutral title 'Mx'. We also ask our candidates if they would like to share their preferred pronouns. This is voluntary but demonstrates our commitment to inclusivity for trans and non binary candidates. Once employed, you can add pronouns and preferred names onto our system.

The University of Derby undertakes anonymised shortlisting during the staff recruitment process. This means that, when shortlisting, panel members will not be able to see an applicant's name and will see an applicant number instead. This demonstrates the practical steps we are taking to remove barriers to recruitment by minimising the possible impact of our unconscious bias.

The University of Derby is committed to safeguarding and promoting the welfare of all our staff, students and children. At the University of Derby, safeguarding is everybody's concern.