AI Vision and Automation Engineer (KTP Associate)

Harper Adams; Edgmond; On-site; GBP 37,000 - 43,000; Full time

Job summary

Karsten UK Limited (Newport facility) invites an Associate to develop an AI-driven vision and quality sorting system using a Fanuc Delta robot on a conveyor rig. The project is a Knowledge Transfer Partnership with Harper Adams University and runs for 24 months with supervision from Harper Adams Collaborative Simulation Laboratory.

The role covers AI model development, simulation-driven data generation, robotic integration and practical engineering delivery in a food processing environment.

Qualifications

• First or upper second-class honours degree in Computer Science, Robotics, Engineering or a closely related discipline.
• Experience developing AI, machine learning or computer vision solutions.
• Programming experience using Python and/or MATLAB.
• Strong communication and project management skills.

Responsibilities

• Develop AI-driven vision and quality sorting capability.
• Create DEM simulations and synthetic training data.
• Train AI classification models achieving high accuracy.
• Integrate outputs with robot controller for automated pick-and-place sorting.

Skills

AI/ML development

Python/MATLAB programming

Project management

Effective communication

Education

Bachelor's degree in Computer Science/Robotics/Engineering

MSc or PhD in a relevant subject

Job description

Location: Karsten UK Limited, Suite 3, Nova House, Audley Avenue Enterprise Park, Newport, Shropshire, TF10 7DW

This post is funded through a Knowledge Transfer Partnership (KTP) between Harper Adams University and Karsten UK Limited, a fresh citrus processing and distribution business supplying major UK and European retailers. The Associate will develop and embed an AI-driven vision and quality sorting capability at Karsten UK’s Newport facility. A Fanuc Delta pick-and-place robot, already owned by Karsten UK, provides the actuation platform. The system will inspect and grade fruit against retailer specifications, using a compact conveyor training rig. The KTP funds the vision and training components, not the robot.

Working from the conveyor training rig, the Associate will develop a Discrete Element Method (DEM) simulation of fruit dynamics, generate synthetic training data through photorealistic rendering, and train AI classification models to achieve 95% accuracy. These outputs will be integrated with the robot controller to enable automated pick-and-place sorting. The approach is product-agnostic and can be retrained for new products and specifications.

The role combines AI model development, simulation-driven data generation, robotic integration, and practical engineering delivery in a food processing environment. Employment will be full-time at Karsten UK's Newport facility, with day-to-day direction from the site team. The Associate will receive at least half a day per week of academic supervision from Harper Adams University and access to its Collaborative Simulation Laboratory. Development, training and validation will take place on the conveyor training rig beside production, with live production reached only after validation on the rig. The post is a 24-month fixed-term appointment, with a target start date of 25 January 2027.

Essential Requirements

• First or upper second-class honours degree in Computer Science, Robotics, Engineering or a closely related discipline.
• Experience developing AI, machine learning or computer vision solutions.
• Programming experience using Python and/or MATLAB.
• Strong communication and project management skills.

Desirable Requirements

• MSc or PhD in a relevant subject area.
• Experience with simulation software, synthetic data generation or robotics.
• Knowledge of industrial automation, PLCs or robot programming.
• Experience within manufacturing, food processing or agricultural sectors.

If you are seeking sponsorship for a Skilled Worker visa, please visit https://www.gov.uk/browse/visas-immigration for further information.

£37,000 to £43,300 per annum (the starting point will depend on relevant qualifications and experience)