ML Ops Platform Lead - Databricks & Lakehouse

BSI; Milton Keynes; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

BSI is hiring a Platform Manager – Machine Learning Operations to oversee the Databricks Lakehouse Platform and MLOps services. The role requires hands-on Databricks administration, CI/CD pipelines, and governance across data and AI workflows.

You will lead incidents, changes, and supplier collaborations while shaping the platform roadmap. You will work in a hybrid setup with monthly in-office presence, coordinating with Data Engineering and Data Science teams to operationalize ML models and

Qualifications

• Proven experience managing data/analytics platforms and/or MLOps in a complex enterprise.
• Hands-on Databricks administration and production support experience.
• Experience implementing MLOps across the model lifecycle (CI/CD, versioning, monitoring).
• Strong stakeholder management and ability to translate business outcomes into priorities.

Responsibilities

• Own and manage the day-to-day operation of the Databricks Lakehouse Platform and MLOps services.
• Lead platform service management: incidents, problems, changes, and requests with escalation.
• Develop and maintain standardized MLOps frameworks, tooling, and best practices.
• Collaborate with Data Engineering and Data Science to operationalize ML models (CI/CD, testing, deployment, monitoring).
• Ensure security, compliance, governance across the platform, including access management and data protection.
• Own the Databricks platform roadmap, drive improvements, cost optimization, and scalable architecture.

Skills

Platform management

Databricks

MLOps

CI/CD

Stakeholder management

Security governance

Supplier management

Cloud platforms

Tools

Databricks workspace

Cluster policies

Delta Lake

Unity Catalog

Job description

BSI is hiring a Platform Manager – Machine Learning Operations to oversee the Databricks Lakehouse Platform and MLOps services. The role requires hands-on Databricks administration, CI/CD pipelines, and governance across data and AI workflows.

You will lead incidents, changes, and supplier collaborations while shaping the platform roadmap. You will work in a hybrid setup with monthly in-office presence, coordinating with Data Engineering and Data Science teams to operationalize ML models and