Machine Learning/AI Engineer (KTP Associate)

The University of Manchester; United Kingdom; Hybrid; GBP 30,000 - 40,000; Full time

Job summary

The University of Manchester is seeking a KTP Associate in Machine Learning and AI to manage a project with Fusion21 Ltd. This role offers a unique opportunity to work on innovative solutions that enhance procurement processes through advanced technologies. Candidates should possess a PhD or strong Master's degree in relevant fields and will benefit from a hybrid working model.

Benefits

Market-leading pension scheme

Employee health and wellbeing services

Generous annual leave entitlement plus bank holidays

Additional paid closure during Christmas

Discounts at major retailers

Qualifications

• PhD or strong Master's degree in Machine Learning, AI, Data Science, Applied Statistics, or Computer Science.
• Relevant experience in Machine Learning and AI is essential.

Responsibilities

• Manage a Knowledge Transfer Partnership project with Fusion21 Ltd.
• Design and implement solutions embedding Machine Learning and AI in procurement.
• Collaborate with a multidisciplinary team to deliver project outcomes.

Skills

Machine Learning

AI

Data Science

Applied Statistics

Software Engineering

Education

PhD or strong Master's degree

Job description

Knowledge Transfer Partnership (KTP) Associate in Machine Learning and AI

This is an exciting opportunity for an ambitious graduate with the ability and confidence to manage a Knowledge Transfer Partnership (KTP) project with Fusion21 Ltd.

The University of Manchester and Fusion21 Ltd are seeking to recruit an individual with a strong background in Machine Learning and AI. The successful candidate will work alongside an MLOps Software Engineer (KTP Associate) to deliver a 24-month project focused on designing and implementing innovative solutions that embed advanced Machine Learning, AI, and software engineering techniques within the procurement process. The project aims to support a data-driven, AI-enhanced business model and information management framework, aligning with the company's digital transformation strategy.

The role offers a unique opportunity to collaborate within a multidisciplinary team of academics and industry practitioners, translating Machine Learning, AI, and Software Engineering techniques into a robust Software/AI-enabled solution.

Candidates should possess a PhD or a strong Master's degree with relevant experience in Machine Learning, AI, Data Science, Applied Statistics, or Computer Science.

This position is funded through a KTP award, a UK Government scheme promoting university-industry collaboration. The role is based at Fusion21 Ltd, located at Unit 2 Puma Court, Kings Business Park, Knowsley, Merseyside, L34 1PJ. The successful candidate will work with supervisors from both the University and Fusion21 Ltd and utilize facilities from both organizations. Fusion21 supports a hybrid working pattern, allowing up to 2 days of remote work per week, subject to line manager approval.

Note: Candidates who have previously completed a KTP are not eligible to apply.

Benefits:

• Market-leading pension scheme
• Employee health and wellbeing services, including an Employee Assistance Programme
• Generous annual leave entitlement plus bank holidays
• Additional paid closure during Christmas
• Discounts at major retailers

We are an equal opportunities employer and welcome applications from all community sections, regardless of age, sex, gender, ethnicity, disability, sexual orientation, or transgender status. All appointments are made based on merit.

Our university supports flexible working arrangements, including hybrid working.

Please note that we do not accept CVs or applications from recruitment agencies. Enquiries from agencies should be directed to [e-mail]. Any CVs submitted by agencies will be considered a gift.

Contact Information:

Enquiries about the vacancy, shortlisting, and interviews:

Name: Dr Tingting Mu

Email: [e-mail]

General enquiries:

Email: [e-mail]

Technical support:

https://jobseekersupport.jobtrain.co.uk/support/home

This vacancy closes at midnight on the specified deadline. Please see the Further Particulars document for detailed person specification criteria.