> Markdown version of [/jobs/ext/1464661-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/1464661-machine-learning-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). --- # Machine Learning Engineer - **Company:** SPG Resourcing - **Location:** Warrington, UK - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, JIRA, Microsoft Azure, Cloud Computing, Cloud Engineering, Continuous Integration, Dataspaces, Python (Programming Language), Machine Learning, Software Engineering, Large Language Models, Generative AI, Git, Kubernetes, Machine Learning Operations, Virtual Agents, Software Version Control, Docker, Databricks - **Published:** July 28, 2026 - **Apply:** https://www.apply4u.co.uk/jobs/x/42187412/ ## About the Role Required skills and experienceCommercial experience in Machine Learning Engineering or Data Science within a production environmentStrong Python development skills with a solid understanding of software engineering best practicesExperience deploying machine learning solutions into cloud-native production environmentsExperience with containerisation technologies such as Docker and orchestration platforms including KubernetesKnowledge of modern MLOps practices including CI/CD, version control (Git) and infrastructure automationExperience working with cloud platforms and modern data ecosystems (Azure and Databricks experience beneficial)Strong understanding of machine learning principles and model deployment processesExcellent communication skills with the ability to explain technical concepts to non-technical stakeholdersExperience working with Agile delivery methodologies and tools such as Azure DevOps and Jira Desirable experienceExperience working with Large Language Models (LLMs), Generative AI or Agentic AI solutions in a commercial environmentExperience deploying machine learning models within regulated industries such as financial services or insuranceExposure to enterprise-scale MLOps and cloud infrastructureExperience contributing to platform architecture and engineering best practices ## Description Machine Learning EngineerLocation: Flexible (Hybrid)Working set up: HybridSalary: Competitive + bonus + benefits SPG are working on behalf of an established financial services organisation investing heavily in its data science and AI capabilities. As part of an expanding team, the business is delivering a range of greenfield machine learning and generative AI initiatives designed to solve real-world business challenges and enhance customer outcomes.This is an exciting opportunity to join a collaborative data function where you'll help shape the organisation's machine learning engineering capability while building scalable, production-ready AI solutions. The RoleWorking as part of a cross-functional Data Science team, the Machine Learning Engineer will play a key role in taking machine learning models from research through to production.You'll work closely with Data Scientists, Data Engineers and Software Engineers to build robust, scalable ML solutions while helping define best practices, tooling and automation across the full machine learning lifecycle.This role is ideal for someone with a passion for software engineering, cloud technologies and productionising machine learning solutions within an enterprise environment. Key responsibilitiesDesign, develop and enhance the organisation's machine learning engineering capability and Data Science platformBuild and automate end-to-end machine learning workflows using CI/CD and Infrastructure as CodeCollaborate with Data Scientists throughout the model development and deployment lifecycleWork closely with engineering teams and business stakeholders to deliver production-ready AI solutionsDevelop high-quality, maintainable Python code following software engineering best practicesContribute to technical design decisions including model deployment strategies and solution architectureSupport the deployment and operationalisation of both traditional machine learning and Generative AI solutionsHelp establish engineering standards, tooling and best practices as the function continues to grow ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Collaboration Quantified: Lessons from Open Source Developer Networks](https://www.wearedevelopers.com/videos/1422-collaboration-quantified-lessons-from-open-source-developer-networks) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How E.On productionizes its AI model & Implementation of Secure Generative AI.](https://www.wearedevelopers.com/videos/623-how-e-on-productionizes-its-ai-model-implementation-of-secure-generative-ai) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [DevOps for Machine Learning](https://www.wearedevelopers.com/videos/179-devops-for-machine-learning) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud)