Digital Manufacturing Engineer for AI based Quality Inspection

Eminox Ltd and the University of Lincoln have been successfully awarded a prestigious Knowledge Transfer Partnership (KTP) funded by Innovate UK. This has created an exciting opportunity to recruit an ambitious KTP Associate to lead an innovative collaborative project between Eminox Ltd and the Creative Automation Lab for Industrial Xfactors (CALIX) , based within the School of Engineering and Physical Sciences at the University of Lincoln. Eminox Ltd is a global leader in the design and manufacture of advanced exhaust aftertreatment systems (EATS) for heavy-duty on-road and off-road vehicles, rail, marine and power generation applications.

Based primarily at Eminox Ltd in Gainsborough, Lincolnshire, you will take a leading technical role in developing and implementing an AI-enabled vision pre-inspection system for industrial manufacturing.

Duties and Responsibilities

You will work to first capture complex, multi-modal industrial datasets to and then develop intelligent methods capable of identifying manufacturing defects and predicting downstream performance outcomes of Diesel Particulate Filter (DPF) units. Combining computer vision, machine learning, deep learning, and industrial automation, you will translate advanced AI research into a robust system capable of operating within a real manufacturing environment.

You will lead activities including developing machine-vision methods for defect detection and classification; designing and training AI models; establishing industrial data pipelines; integrating AI algorithms with manufacturing processes; and validating and optimising the resulting system under industrial operating conditions. The aim is to improve inspection accuracy and consistency while reducing unnecessary downstream processing, manufacturing costs and waste.

This is much more than a desk-based AI role. You will work at the interface between advanced research and industrial implementation, developing prototypes, conducting system-integrated testing, and translating theoretical approaches into commercially viable solutions.

Education, Skills and Experience

We are looking for an ambitious interdisciplinary engineer who wants to apply advanced digital technologies to real industrial challenges.

• A strong academic foundation: A master’s degree in mechanical engineering, Manufacturing Engineering, Robotics, Artificial Intelligence, Computer Science/Data Science, or a closely related discipline is essential. A PhD in a relevant discipline is desirable.
• AI and data expertise: Experience in machine learning, computer vision and/or data analytics, with an ability to develop and evaluate intelligent models for engineering applications.
• Strong programming capability: Programming experience in Python or similar is particularly important, with MATLAB or similar environments also relevant. Experience with deep-learning frameworks such as PyTorch or TensorFlow and computer-vision tools such as OpenCV would be advantageous.
• Engineering and experimental capability: Experience of experimental work, quality-inspection techniques, and systems, and researching and developing new or improved engineering systems or methods.
• Analytical problem-solving: Strong mathematical, critical-thinking, and problem-solving skills, with the ability to analyse complex data and translate technical concepts into practical industrial solutions.
• Industrial and digital manufacturing experience: Familiarity with industrial datasets, manufacturing environments, process automation and control systems such as PLCs, Industry 4.0 technologies or automated quality-inspection systems would be advantageous.
• Project leadership: The ability to manage a complex project involving multiple stakeholders, organise your own work effectively and deliver against demanding KTP and business milestones.
• A collaborative and innovative mindset: You should be proactive, adaptable, and enthusiastic about R&D, with the ability to work independently while collaborating effectively with multidisciplinary academic and industrial teams.

The project provides an unusual opportunity for an ambitious engineer or AI specialist to become the technical lead for a strategically important industrial innovation project, developing expertise that bridges advanced AI research and manufacturing practice.

As the KTP Associate, you will have considerable autonomy and responsibility for delivering the project, managing technical milestones, and communicating results. You will also contribute to research outputs, technical reports, publications, and conference presentations, while developing documentation and training materials that enable the new knowledge and capability to remain embedded within Eminox beyond the project.