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# AI Engineer

- **Company:** Harnham
- **Location:** London, UK (Remote available)
- **Salary:** £130,000.0 - £156,000.0
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Continuous Integration, DevOps, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Pytorch, Large Language Models, Scikit Learn, Machine Learning Operations
- **Published:** September 11, 2026
- **Apply:** https://www.reed.co.uk/jobs/ai-engineer/57333929

## About the Role

* Strong experience developing and deploying machine learning models in production environments.
 * Excellent Python development skills and experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
 * Experience working with cloud platforms such as AWS, Azure, or GCP.
 * Strong understanding of MLOps, CI/CD principles, and model lifecycle management.
 * Experience building scalable data and AI solutions using modern engineering practices.
 * Ability to communicate technical concepts effectively to both technical and non-technical stakeholders.
 * Experience within a consumer goods, retail, e-commerce, or FMCG environment would be advantageous.

## Description

They are a well-established consumer goods business with a strong international presence and a growing investment in AI and advanced analytics. Data and technology are central to their strategy, with multiple initiatives focused on automation, personalisation, and operational efficiency. You will work within a collaborative environment where innovation is encouraged and modern machine learning technologies are actively adopted.

The Role and Deliverables

 * Build, deploy, and maintain machine learning models for a range of business use cases.
 * Develop scalable AI solutions that support customer, marketing, supply chain, and commercial functions.
 * Work closely with data scientists, data engineers, and business stakeholders to translate requirements into production-ready solutions.
 * Implement MLOps best practices to support model deployment, monitoring, and performance optimisation.
 * Evaluate and integrate emerging AI technologies, including generative AI and large language models where appropriate.
 * Support the development of a robust machine learning infrastructure and technical roadmap.


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