AI Programmer / Developer – Machine Learning and Neural Networks

Location

Centre for Factories of the Future (C4FF), Berkeley House, 6 The Square, Kenilworth, Warwickshire CV8 1EB

Job type

Full-time

Salary

£35,000–£45,000 per annum, depending on qualifications and relevant experience

Reporting to

Dr Lakhvir Singh and the C4FF Senior Management Team

About C4Ff

The Centre for Factories of the Future (C4FF) delivers UK and international research and innovation projects involving AI, advanced manufacturing, child-protection technology, sustainability, agriculture and intelligent decision support. We collaborate with universities, businesses, public bodies and international partners.

Our portfolio includes

· Lean Optimal

• using AI to improve manufacturing efficiency, reduce material waste and avoidable energy use, and support operational decisions.

· CSAM Guard Plus

• developing responsible AI technologies to support child protection and safer online environments for children.

· FERIDE

• applying AI, Earth-observation data and decision-support technologies to regenerative agriculture, soil management and soil-carbon monitoring.
• Other AI, manufacturing, sustainability, agriculture and online-safety projects.

The Role

C4FF is seeking an experienced, hands-on AI Programmer/Developer to design and develop advanced AI solutions across its research and innovation portfolio.

This is an AI software and model-development role, not a conventional data-analysis or business-intelligence position. The successful candidate will build, train, evaluate, integrate and improve machine-learning and neural-network models, converting prototypes into reliable applications.

Lean Optimal, CSAM Guard Plus and FERIDE are all organisational priorities. The successful candidate may work across several projects concurrently.

Candidates must demonstrate strong hands-on Python, software-engineering and machine-learning capabilities. Data-science and statistical skills are valuable when supporting model development and evaluation.

Experience limited mainly to reporting, dashboards, routine analytics or using pre-built AI services without substantial programming and model-development responsibility will not, by itself, be sufficient.

Key Responsibilities

AI and machine-learning development

• Design, programme, train, test and improve AI and machine-learning models.
• Develop neural-network solutions using PyTorch, TensorFlow, Keras or similar frameworks.
• Select and implement suitable architectures for classification, regression, prediction, anomaly detection, optimisation, computer vision, NLP or time-series modelling.
• Create reproducible data-preparation, training, validation, testing and inference pipelines.
• Undertake feature engineering, model selection and hyperparameter optimisation; investigate data leakage, overfitting and concept drift; and assess robustness, bias and explainability.
• Research new approaches and develop promising prototypes into reliable software.

AI software engineering

• Write efficient, maintainable, secure and well-documented Python code.
• Design modular and reusable AI components.
• Convert experimental work into structured, tested software and integrate models through APIs into applications, databases and decision-support systems.
• Use Git/GitHub or similar tools for version control, code review and collaboration.
• Diagnose technical problems and support deployment, monitoring and maintenance using databases, cloud services, containers and data pipelines where required.

Data science and statistics

• Explore complex datasets, establish sound baselines and apply appropriate experimental-design and validation methods.
• Address missing data, outliers, class imbalance, sampling bias and leakage; select suitable metrics; and communicate uncertainty and limitations.

Project contributions

• Lean Optimal: develop and validate predictive and optimisation models using manufacturing, quality, material and energy data.
• CSAM Guard Plus: develop responsible AI capabilities supporting child protection, including robust evaluation, explainability, human oversight, safeguarding, privacy and security.
• FERIDE: develop AI using farm, soil, weather, sensor and Earth-observation data, supporting soil-carbon monitoring and explainable decision-support tools.
• Apply AI programming, model-development and statistical capabilities to other C4FF projects.

Research delivery and leadership

• Translate partner requirements into technical tasks and contribute to plans, deliverables, pilots, reports, demonstrations and funding proposals.
• Work with multidisciplinary and international partners; document technical work; identify risks; and mentor graduate developers.
• Follow C4FF’s cybersecurity, GDPR, safeguarding, responsible-AI and quality procedures.

Essential Qualifications And Experience

• A relevant Master’s or PhD; alternatively, a relevant first degree with substantial professional AI experience.
• Normally at least four years of relevant professional or substantial applied-research experience involving hands-on AI or machine-learning development.
• Strong Python skills and experience developing substantial AI or machine-learning software.
• Practical experience designing, training, testing and evaluating machine-learning or neural-network models.
• Experience with PyTorch, TensorFlow or Keras and libraries such as Scikit-learn, Pandas, NumPy or SciPy.
• Sound knowledge of neural-network training, optimisation, regularisation, validation and evaluation.
• Experience creating repeatable data-preparation and model-training pipelines using real-world data.
• Strong software-engineering skills, including modular design, testing, debugging, documentation and version control.
• Experience integrating AI models into applications, APIs, services or demonstrators.
• Ability to implement research methods, diagnose technical problems and improve existing models.
• Strong analytical, communication and problem-solving skills.
• Ability to work independently, manage several projects and contribute to multidisciplinary and international teams.
• Eligibility to work in the United Kingdom.

Candidates with fewer than four years of post-university professional experience may be considered if they hold a relevant PhD and demonstrate substantial hands-on AI programming, model development, software engineering and practical delivery through doctoral or postdoctoral research.

A PhD alone does not replace the need for practical AI-development capability.

Desirable Qualifications And Experience

Advanced AI and software development

• More than four years of commercial, industrial or applied-research AI-development experience.
• Experience leading an AI system from experimentation into a working or deployed application.
• Advanced neural-network and deep-learning experience.
• Experience in computer vision, NLP, time-series forecasting, anomaly detection, predictive modelling, optimisation, explainable AI, generative AI or Large Language Models.

Data science and statistics

• Strong exploratory analysis and visualisation skills, with knowledge of descriptive and inferential statistics, probability and uncertainty.
• Experience with experimental design, hypothesis testing, regression, classification, clustering or time-series analysis.
• Understanding of correlation, causation, confounding, cross-validation, bootstrapping and calibration.
• Experience selecting measures such as precision, recall, F1, sensitivity, specificity and ROC-AUC.

Systems and project experience

• Experience with SQL, APIs, cloud platforms, Docker, CI/CD, MLOps or model monitoring.
• Understanding of secure AI, GDPR, responsible AI, safeguarding and research ethics.
• Experience working on Innovate UK, Horizon Europe, Eureka, ITEA or other publicly funded research and innovation projects.
• Experience collaborating with universities, SMEs, manufacturers or international research partners.
• Experience preparing project deliverables, technical work packages, reports or grant applications.
• Experience supervising or mentoring junior AI developers, researchers or graduates.
• Evidence of AI software, repositories, publications or deployed systems.

Applicants are not expected to have experience in every C4FF sector. Strong AI programming and model-development capability, combined with the ability to learn new domains and work with subject-matter experts, is more important.

Application Requirements

Please provide

• A current CV.
• A short description of one model, including its architecture, your contribution, evaluation and deployment.
• Confirmation of your eligibility to work in the United Kingdom.

Shortlisted candidates may be asked to discuss previous AI code and model-development work and complete a proportionate technical exercise.

Application Timeline

Application deadline

11:00 am on Friday 18 September 2026

• Interviews:

Wednesday 23 September 2026