KTP Associate - Machine Learning and Vision Systems Engineer

Spotted & Shared by Gradsouthwest; Bristol; On-site; GBP 30,000 - 40,000; Full time

Job summary

A leading educational institution in Bristol is seeking a full-time AI developer to enhance nursery safety through machine vision and AI. You will collaborate with Family Adventures Group to drive innovations in childcare. Candidates should have a relevant degree and solid skills in machine learning and Python. This 30-month role offers extensive training and development opportunities, emphasizing a supportive and diverse work environment.

Benefits

£2,000 annual training budget

Comprehensive development opportunities

Qualifications

• 1st or 2:1 degree in a relevant field.
• Strong skills in model design, training, and image/video processing.
• Comfortable working with hardware like cameras and edge devices.

Responsibilities

• Lead and develop AI capabilities to enhance nursery safety.
• Drive proactive prevention and reactive response in early-years settings.

Skills

Machine learning

Machine vision

Python programming

Data handling

Education

Degree in AI, Computer Vision, Machine Learning, Data Science, or Robotics

Job description

About this role

About this role This is an exciting opportunity to work in a collaborative partnership between the University of the West of England (UWE Bristol) and Family Adventures Group Ltd under the UK Government sponsored Knowledge Transfer Partnership (KTP) programme.

This is a 30-month fixed-term role offering comprehensive development opportunities, including residential management and business training through the national KTP programme at Ashorne Hill, plus a £2,000 annual training budget for tailored personal development. You’ll be based at our multi-award winning partner, Family Adventures Group, who specialise in childcare and leisure across the South West, Midlands, and Wales.

They focus on delivering high-quality early years education through their nursery brands and run immersive indoor play centres. Supported by academics from UWE Bristol’s Centre for Machine Vision, you will lead and develop AI capabilities to enhance safety and reduce risk in early-years nursery settings through both proactive prevention and reactive response.

About you

About you

Degree (1st or 2:1) or equivalent in AI, Computer Vision, Machine Learning, Data Science (ML specialisation) or Robotics.

• Strong knowledge and skills in machine learning (model design, training, and evaluation) and machine vision (image/video acquisition and processing). Comfortable working with hardware (cameras and edge devices) and proficiency in programming languages commonly used in AI, (Python).
• Skilled in data handling: collection, cleaning, preprocessing, and annotation workflows.
• Eligibility for enhanced DBS or equivalent safeguarding clearance, required for working in nursery environments with children.

Where you will be working

This role based at Family Adventures Group Ltd, Weston Super-Mare.

Why UWE Bristol?

We are one of the largest providers of Higher Education in the South West with 38,000 students and 4,000 staff from right across the globe. Based in vibrant Bristol, our ambitions are to make a positive difference to our planet, transforming futures through actions and solving real world challenges.

Add your individuality to ours

UWE Bristol recognises the power of a truly diverse university community.

We’re part of a vibrant, multicultural city and welcome talented people from all backgrounds. Diversity is our strength, enhancing creativity, decision making, and problem solving. Join our supportive community and thrive.

We particularly encourage applications from global majority candidates as we are currently under-represented in this area, however all appointments are made strictly on individual merit.

As a Disability Confident employer we welcome applications from those who identify as having a disability.

Further information

If you would like to speak to us to find out more about this role, please contact Wenhao Zhang email: [e-mail]

This is a full-time, fixed-term post for 30 months, working 40 hours per week.