The job requirements are detailed below. Where applicable the skills, qualifications and memberships required for this job have also been included.
Job details
Job reference: REQ0001838
Date posted: 04/02/2025
Application closing date: Midnight 03/03/2025
Location: Leeds
Salary: Up to £42,000 depending on skills and experience
Package: Please refer to Candidate Pack
Job category/type: Administrative/Support, Professional/Managerial
Machine Learning Engineer (Fixed term 33 months)
We are seeking an ambitious, talented and motivated individual to be at the centre of an innovative KTP project with ARC Building Solutions Ltd – the UK’s leading manufacturer of cavity fire barriers and cavity closers.
This 33-month project will see you work with ARC and academics from the School of Built Environment, Engineering and Computing at Leeds Beckett University to create a bespoke, quality and installation monitoring product utilising AI predictive model development and data monitoring. The product will optimise installation quality, automate fault finding and be underpinned by dynamic digital asset management.
ARC is the UK’s leading manufacturer of cavity fire barriers and cavity closers: the only UK manufacturer of low-rise cavity barriers to hold internationally recognised third-party IFC certification. ARC collaborates with industry partners to solve challenges across new build, retrofit, low-rise, high-rise and insulation sectors. This agile approach positions ARC as part of the avant-garde of construction product manufacturers. Founded in 2008, ARC’s offices and manufacturing facility is based in Gildersome, Leeds. The successful candidate will be based at the company premises and will feel, to all intents and purposes, part of the ARC team.
This innovative project is vital in fulfilling ARC’s longer-term strategic ambition to achieve more regulated assurance that their fire prevention products are correctly installed. The development of this solution has the potential to revolutionise the current building-site industry practices and address key recommendations within the Hackitt Report.
We encourage applications from a graduate with a good first degree in Computer Science, Engineering, Construction Informatics, Data Analytics, or a related field. Higher degrees would be advantageous. Relevant professional experience and certification in software development and machine learning will also be considered.
Excellent project management skills, proactive problem-solving abilities, and strong interpersonal skills with the ability to engage and influence multiple stakeholders are all qualities which the successful candidate should bring.
To apply for this role, please select 'Apply online' below and complete the short application form. Please also attach an updated CV and a covering letter of no more than two sides of A4 paper outlining how your education, skills and experience make you suitable for this role - where possible please address the specific requirements of the role as per the Employee Specification and outline your own suitability with relevant examples.
We ask you not to use an AI assistant model such as Chat GPT to generate your CV or cover letter.
Working here means you’ll also have access to a wide range of benefits including our generous pension schemes, excellent holiday entitlements, flexible working, reduced study fees, subsidised fitness facilities and a lot more.
We welcome applications from all individuals and particularly from black and global majority candidates as members of these groups are currently under-represented at this level of post. All appointments will be based on merit.
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