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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # MLOps AI Lead & Databricks Platform Specialist - **Company:** DSR Global Ltd - **Location:** London, UK - **Experience:** Expert - **Salary:** £87,447.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Business Analytics Applications, Automation of Tests, Continuous Integration, Information Engineering, Identity and Access Management, Machine Learning, Release Management, Management of Software Versions, System Availability, Build Management, Data Lakes, Machine Learning Operations, Databricks - **Published:** August 29, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5859784065 ## About the Role * 3 - 5 years' experience * Proven experience managing data/analytics platforms and/or MLOps capabilities in a complex enterprise environment. * Hands-on experience operating Databricks (workspace administration, cluster policies, jobs, Delta Lake, Unity Catalog, access controls, and production support) * Experience implementing MLOps practices across the model lifecycle (CI/CD, versioning, monitoring, reproducibility) * Strong stakeholder management; able to translate business outcomes into platform priorities and service commitments. * Experience working with security, risk, and governance teams to evidence controls for data and AI services * Experience managing suppliers and delivery partners, including service performance and support processes. * Heavy on Databricks ## Description We are currently seeking an MLOps AI Lead & Databricks Platform Specialist to join a global end client, taking ownership of the Databricks platform and supporting the delivery of robust, scalable MLOps capabilities., * Own and manage the day-to-day operation of the Databricks Lakehouse Platform and MLOps services, ensuring high availability, performance, security, and user satisfaction. * Lead platform service management activities, including incident, problem, change, and request processes, while coordinating support and escalation procedures. * Develop and maintain standardized MLOps frameworks, tooling, and best practices to support the end-to-end machine learning lifecycle. * Collaborate with Data Engineering and Data Science teams to operationalize ML models through CI/CD, automated testing, deployment, and monitoring capabilities. * Ensure robust security, compliance, and governance controls across the platform, including access management, data protection, audit readiness, and risk mitigation. * Own the Databricks platform roadmap, driving continuous improvement, technical standards, cost optimization, and scalable architecture patterns. * Manage vendor and supplier relationships, overseeing service performance, support activities, release planning, and commercial considerations. * Act as the primary platform stakeholder interface, providing guidance, training, documentation, and enablement to help teams effectively build and deploy data and AI solution ## Related Videos - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) - [Enabling intelligent logistics automation: home-grown Industrial IoT platform at Austrian Post](https://www.wearedevelopers.com/videos/2018-enabling-intelligent-logistics-automation-home-grown-industrial-iot-platform-at-austrian-post) ## Related Articles - [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 – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [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) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)