> Markdown version of [/jobs/ext/3840059-senior-ml-engineer](https://www.wearedevelopers.com/jobs/ext/3840059-senior-ml-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior ML Engineer - **Company:** Harnham - **Location:** London, UK - **Experience:** Expert - **Salary:** £95,000.0 - £96,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computer Vision, Big Data, Information Engineering, Machine Learning, Natural Language Processing, Standard Sql, Unstructured Data, Feature Store, Large Language Models, Generative AI, Backend, Build Management, Machine Learning Operations, Data Pipelines - **Published:** October 20, 2026 - **Apply:** https://www.reed.co.uk/jobs/senior-ml-engineer/57474766 ## About the Role * Strong commercial experience within Machine Learning Engineering, Data Science, or MLOps * Experience deploying, monitoring, and maintaining machine learning models in production environments * Strong SQL and data engineering capabilities, with experience working on large-scale datasets * Interest in AI technologies, including NLP, Computer Vision, LLMs, or Generative AI applications * Experience building scalable data pipelines and ML systems * Strong communication skills and the ability to work effectively across technical and non-technical teams ## Description * Build and deploy production machine learning models that support large-scale automation and decision-making * Design and optimise data pipelines, backend services, and ML infrastructure * Develop and maintain feature stores and model-serving capabilities for real-time and batch use cases * Take ownership of projects from problem definition through to production deployment and monitoring * Work with structured and unstructured data to solve complex business challenges * Collaborate with Data Scientists, Software Engineers, and Product teams to deliver scalable solutions * Contribute to the development of greenfield machine learning products and capabilities * Drive best practices across MLOps, monitoring, observability, and model lifecycle management