MLOps AI Lead & Databricks Platform Specialist

DSR Global; Slough; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

DSR Global is seeking an MLOps AI Lead & Databricks Platform Specialist to own the Databricks Lakehouse Platform and drive robust MLOps capabilities across the enterprise. The role involves platform service management, security governance, and collaborating with Data Engineering and Data Science teams to operationalize ML models through CI/CD, testing, deployment and monitoring.

The position is hybrid, with 2-3 days onsite in London (Covent Garden) or Milton Keynes.

Qualifications

• 3–5 years’ experience in data/analytics platforms or MLOps.
• Hands-on Databricks administration and production support.
• Experience implementing MLOps across model lifecycle (CI/CD, versioning, monitoring).
• Strong stakeholder management; translate business outcomes into platform priorities.
• Experience with security, risk and governance for data and AI services.
• Experience managing suppliers and delivery partners, including service performance.

Responsibilities

• Own and manage day-to-day operation of the Databricks Lakehouse Platform and MLOps services.
• Lead platform service management activities: incident, problem, change, and request processes.
• Develop and maintain standardized MLOps frameworks, tooling, and best practices.
• Collaborate with Data Engineering and Data Science to operationalize ML models through CI/CD, testing, deployment, monitoring.
• Ensure robust security, compliance and governance controls across the platform.
• Own Databricks platform roadmap, drive improvement, standards, cost optimization, scalable patterns.
• Manage vendor and supplier relationships, overseeing performance and support.

Skills

MLOps practices

CI/CD pipelines

Stakeholder management

Security governance

Vendor management

Platform roadmap

Tools

Databricks

Job 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.

We are ideally looking for someone on a permanent basis, although contract-to-permanent could also be considered.

Location: Hybrid – 2 -3 days per week onsite in London, Covent Garden / Milton Keynes.

Experience required:

• 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

Key Responsibilities:

• 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