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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Engineer - **Company:** Deloitte - **Location:** Glasgow, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Automation of Tests, Microsoft Azure, Cloud Engineering, Continuous Integration, Information Engineering, Monitoring of Systems, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Azure Machine Learning, Pytorch, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Model Validation, Generative AI, Build Management, Scikit Learn, Information Technology, Xgboost, Machine Learning Operations, Software Version Control, Data Pipelines, Programming Languages - **Published:** August 1, 2026 - **Apply:** https://apply.deloitte.co.uk/UKCareers/Login?jobId=24438 ## About the Role We are looking for candidates who are able to demonstrate skills and experience in some of the following, * Degree or equivalent experience in Computer Science, Data Engineering, Mathematics, Artificial Intelligence, Machine Learning or a related discipline. * Hands-on experience designing, developing and deploying AI, machine learning or Generative AI solutions in a consulting, commercial or technology delivery environment. * Experience working with business and technical stakeholders to understand requirements, shape solution options and deliver measurable outcomes. * Proven ability to own technical deliverables or workstreams, manage delivery priorities and communicate progress clearly to project teams and stakeholders. * Experience working in data-intensive, regulated or complex enterprise environments is advantageous. BUSINESS & AI PROFICIENCY * Strong proficiency in Python or another modern programming language used for AI/ML development, with practical experience across model development, testing and deployment. * Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. * Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. * Understanding of MLOps and production AI practices, including CI/CD, model versioning, monitoring, automated testing, retraining and performance optimisation. * Experience using cloud platforms and cloud-native AI/ML services, such as Azure, AWS or GCP, to build and deploy scalable solutions. * Strong communication and collaboration skills, with the ability to explain technical concepts to both engineering teams and non-technical stakeholders. ## Description We are seeking to hire talented AI/ML Engineers within our AI Scaling and Transformation team, a centre of excellence in Deloitte's Engineering, AI & Data service offering. You will work alongside clients, third parties and Deloitte teams from across the Firm, supporting organisations as they design, build and scale AI-enabled solutions. This is a hands-on engineering role where you will combine strong technical capability with client-facing delivery, helping to translate business needs into production-ready AI and machine learning systems. As an AI/ML Engineer, you will play a key role in designing, developing and delivering data and AI solutions for our clients. In this role, you may be expected to: * Work with client stakeholders, product owners and Deloitte teams to understand business challenges and translate them into practical AI/ML solution designs. * Design, build, test and deploy machine learning models, Generative AI components, data pipelines and analytics solutions that are robust, scalable and maintainable. * Take ownership of technical deliverables or workstreams, ensuring engineering outputs are aligned to agreed requirements, delivery plans and quality standards. * Support the deployment and operationalisation of AI systems, including model monitoring, performance optimisation, CI/CD and MLOps practices. * Collaborate with solution architects, data scientists, business analysts and engineers to ensure AI solutions are integrated effectively into wider technology and business environments. * Apply responsible AI, security, privacy and governance considerations throughout the development lifecycle. * Contribute to the development of junior team members by sharing engineering knowledge, reviewing outputs and supporting a culture of continuous improvement. ## Related Videos - [Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More](https://www.wearedevelopers.com/videos/869-inside-the-ai-revolution-how-microsoft-is-empowering-the-world-to-achieve-more) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [TikTok's Privacy Innovation](https://www.wearedevelopers.com/videos/1036-tiktok-s-privacy-innovation) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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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) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)