ML Software Engineer (KTP Associate) — Data-Driven Impact

The Knowledge Transfer Network Limited; Ipswich; Hybrid; GBP 42,000 - 62,000; Full time

Benefits offered by this job

Personal development budget

Mentoring by Innovate UK KTP Adviser

Access to university resources

Exposure to diverse stakeholders

Job summary

Distag QCS in partnership with the University of Essex is seeking a Machine Learning Software Engineer (KTP Associate) to design and implement advanced data-driven solutions within a manufacturing and supply chain context.

You will work on large ERP-derived datasets, build reliable ML models, and help translate research into practical decisions while collaborating with stakeholders across manufacturing and supply chain domains.

Qualifications

• MSc in Data Science, Machine Learning, or similar.
• Knowledge/experience of computational/artificial intelligence.
• Understanding of UI centred product design, data extraction and interrogation.
• Knowledge/interest in deep learning and neural networks.
• Knowledge/interest in optimisation, modelling and algorithm development.
• Strong mathematical foundation.
• Understanding of project management and leadership.
• Experience of project management (highly desirable).
• Experience of working in a supply chain/wholesale environment.

Responsibilities

• Lead the thinking and set the pace for data-driven initiatives.
• Work with stakeholders to translate insights into practical decisions.
• Build reliable ML models from large ERP-derived data sources.
• Balance hands-on development with real-world business constraints.

Skills

Python programming

Data interpretation

Communication

English proficiency

ML knowledge

Project management

Education

MSc in Data Science, Machine Learning, or similar

Tools

None

Job description

Distag QCS in partnership with the University of Essex is seeking a Machine Learning Software Engineer (KTP Associate) to design and implement advanced data-driven solutions within a manufacturing and supply chain context.

You will work on large ERP-derived datasets, build reliable ML models, and help translate research into practical decisions while collaborating with stakeholders across manufacturing and supply chain domains.