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Machine Learning/AI Engineer (KTP Associate)

The University of Manchester - Science and Engineering - Department of Computer Science - School of Engineering

Location: Manchester
Salary: £46,735 to £57,422 per annum depending on relevant experience
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 22nd May 2025
Closes: 16th June 2025
Job Ref: SAE-028736
Job reference: SAE-028736
Salary: £46,735 - £57,422 per annum depending on relevant experience
Faculty/Organisational Unit: Science and Engineering
Location: -
Employment type: Fixed Term
Division/Team: Department of Computer Science
Hours Per Week: Full Time (1FTE)
Closing date (DD/MM/YYYY): 16/06/2025
Contract Duration: 24 Months
School/Directorate: School of Engineering

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 looking to recruit an individual with evidence of a strong grounding in Machine Learning and AI who will work alongside an MLOps Software Engineer (KTP Associate) to collaboratively deliver this 24-month project. The project aims to design and deliver a disruptive technical innovation programme that embeds advanced Machine Learning, AI and software engineering techniques within the procurement process and supports the incorporation of a data-driven AI-enhanced business model and information management framework, supporting the company's strategic vision for digital transformation.

The position will provide the successful candidate with a unique opportunity to work within a multi-disciplinary team of academics, industry practitioners and another KTP associate, and translate Machine Learning, AI, and Software Engineering techniques to deliver a robust Software/AI enabled solution.

Candidates will require a PhD or a very strong Masters degree with relevant work/project experience in Machine Learning, AI, Data Science, Applied Statistics, Computer Science.

This post is funded through a Knowledge Transfer Partnership (KTP) award, a UK Government scheme intended to promote sustained and mutually beneficial relationships between universities and industry.

Based at Fusion21 Ltd, Unit 2 Puma Court, Kings Business Park, Knowsley, Merseyside, L34 1PJ the successful candidate will work directly with supervisors from both the University and Fusion21 Ltd and will use the facilities and resources of both organisations. Fusion21 follows a hybrid working pattern and role will offer some flexibility to work from home, but this cannot exceed 2 days in a working week and is subject to line manager approval.

Due to the nature of the funding, KTP Associates who have already completed a KTP are not eligible to apply.

What you will get in return:

  • Fantastic market leading Pension scheme
  • Excellent employee health and wellbeing services including an Employee Assistance Programme
  • Exceptional starting annual leave entitlement, plus bank holidays
  • Additional paid closure over the Christmas period
  • Local and national discounts at a range of major retailers

As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.

Our University is positive about flexible working – you can find out more here

Hybrid working arrangements may be considered.

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.

Any recruitment enquiries from recruitment agencies should be directed to People.Recruitment@manchester.ac.uk.

Any CVs submitted by a recruitment agency will be considered a gift.

Enquiries about the vacancy, shortlisting and interviews:

Name: Dr. Tingting Mu

Email: tingting.mu@manchester.ac.uk

General enquiries:

Email: People.recruitment@manchester.ac.uk

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

This vacancy will close for applications at midnight on the closing date.

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