KTP Associate - Digital Manufacturing Engineer for AI based Quality Inspection

Lincoln Institute; Gainsborough CP; Hybrid; GBP 32,000 - 42,000; Full time

Job summary

Eminox Ltd. and the University of Lincoln are offering a KTP Associate role to develop an AI-enabled vision pre-inspection system for industrial manufacturing. You will lead data collection, model development, and integration with production lines, working across academic and industrial teams.

The role emphasizes autonomy, collaboration, and delivering industrially viable AI solutions within a 24-month programme at Eminox in Gainsborough.

Qualifications

• Master’s degree in mechanical engineering or AI-related field is essential.
• Experience with ML, CV and data analytics for engineering apps.
• Programming in Python; familiarity with PyTorch/TensorFlow and OpenCV advantageous.

Responsibilities

• Develop AI-enabled vision pre-inspection system for manufacturing.
• Capture multi-modal industrial datasets and build intelligent models.
• Lead AI model design, data pipelines and integration with processes.
• Validate system under industrial conditions and produce documentation.

Skills

Python

ML

CV

Data analytics

Industrial automation

OpenCV

PyTorch

Project leadership

Education

Master's in Mechanical Eng / AI / CS

PhD desirable

Tools

Python

TensorFlow

OpenCV

MATLAB

Job description

KTP Associate - Digital Manufacturing Engineer for AI based Quality Inspection

Knowledge Transfer Partnerships

Location: Off Campus
Please note, this post is fixed-term until 31/10/2028 and full-time at 37 hours per week.
Closing Date: Friday 30 October 2026
Interview Date: To be confirmed
Reference: EL1284

Are you passionate about applying artificial intelligence and computer vision to solve real-world manufacturing challenges? Do you want to take cutting-edge AI technologies beyond the laboratory and deploy them within a live industrial environment? Are you excited by the opportunity to lead an innovation project at the intersection of AI, digital manufacturing, and industrial automation?

We are seeking a KTP Associate - Digital Manufacturing Engineer for AI-Based Quality Inspection for an exciting 24-month Knowledge Transfer Partnership (KTP) between the University of Lincoln and Eminox Ltd.

Eminox is a global leader in the design and manufacture of advanced exhaust after-treatment systems for heavy-duty on-road and off-road vehicles, rail, marine and power-generation applications. This KTP brings together Eminox's industrial expertise with research expertise from the University of Lincoln's Creative Automation Lab for Industrial X-factors (CALIX) in intelligent manufacturing, industrial automation, artificial intelligence, computer vision and Industry 4.0 technologies.

What You'll Be Doing

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.

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.

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.

What We're Looking For

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.

Why Join Us?

This KTP offers a unique opportunity to lead the development of an industrial AI system from research concept through to implementation in a live manufacturing environment.

You will benefit from:

• Direct mentorship and joint supervision from experienced engineers and senior management at Eminox and academic experts from the University of Lincoln.
• Access to a dedicated KTP personal development and training budget.
• Nationally recognised management and leadership development through the Innovate UK KTP programme.
• Experience spanning AI, computer vision, digital manufacturing, industrial automation, and real-world technology deployment.
• Opportunities to produce research outputs and engage with the wider academic and industrial research community.
• The opportunity to develop project-management, leadership, and stakeholder-engagement capabilities alongside your technical expertise.
• Strong potential for continued career development within Eminox following successful completion of the KTP.

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.

The role is based primarily at Eminox Ltd in Gainsborough, Lincolnshire, with regular interaction with the University of Lincoln and CALIX. The Associate will work closely with both industrial and academic teams throughout the 24-month project.

If you would like further information or an informal discussion about this exciting opportunity, please contact Dr Faiz Iqbal ([e-mail]), School of Engineering and Physical Sciences, University of Lincoln.

Further details:

• Job Description and Person Specification

You can find out more about working at Lincoln, and everything that we have to offer, at:

https://www.lincoln.ac.uk/jobopportunities/

We strive for a diverse workforce with the very best employees and are committed to creating an inclusive environment for all. The University encourages applications from underrepresented groups inclusive of Black, Asian and other minoritised/marginalised ethnic groups, all gender identities and expressions from the LGBTQIA+ community, candidates with a disability, and those that practise different faiths and beliefs, to enhance our One Community where we strive to be kind, patient, and supportive of each other.

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