Role 1:
Role Title: Senior ML Platform Consultant
Location: London, UK
Days on site: 2-3 days a week
Role Description:
Senior ML Platform Consultant (Hands-on Lead)
**Purpose:** Lead the discovery and pilot migration while actively contributing to architecture, engineering, and delivery activities.
**Key Responsibilities**
- Perform hands-on assessment of Azure ML models, pipelines, dependencies, and operational processes.
- Review existing Global AI Platform capabilities and identify required enhancements.
- Define migration patterns, standards, and technical approach.
- Lead delivery of the pilot migration for two selected models.
- Coordinate activities across Azure ML, Databricks, and platform engineering resources.
- Produce recommendations, migration roadmap, and reusable assets.
**Key Experience**
- Azure ML and enterprise MLOps platforms.
- ML platform migration experience.
- Strong engineering background with hands-on delivery experience.
Role 2:
Role Title: MLOps Engineer-Azure ML Specialist
Location: London, UK
Days on site: 2-3 days a week
Role Description:
MLOps Engineer (Azure ML Specialist)
**Purpose:** Assess and document the existing Azure ML estate and support migration of workloads.
**Key Responsibilities**
- Investigate current Azure ML development patterns and Data Scientist workflows.
- Analyse training pipelines, deployment pipelines, model artefacts, and monitoring capabilities.
- Document dependencies, integrations, and data flows.
- Extract and transition model assets, configurations, and deployment patterns.
- Support migration and testing of pilot models.
- Provide recommendations for migration and optimisation.
**Key Experience**
- Strong hands-on Azure ML experience.
- Python and machine learning frameworks.
- Azure DevOps, CI/CD, and model lifecycle management.
Experience supporting production ML workloads
Role 3:
Role Title: MLOps Engineer-(Databricks Specialist)
Location: London, UK
Days on site: 2-3 days a week
Role Description:
MLOps Engineer (Databricks Specialist)
**Purpose:** Implement ML workloads and MLOps capabilities on the Global AI Platform.
**Key Responsibilities**
- Configure and optimise Databricks-based ML development and deployment frameworks.
- Implement model training, deployment, monitoring, and governance capabilities.
- Adapt or develop frameworks required to support migrated workloads.
- Build CI/CD pipelines and automation for ML lifecycle management.
- Lead technical implementation of pilot models on the Global AI Platform.
- Develop reusable migration accelerators and standards.
**Key Experience**
- Databricks Lakehouse Platform.
- Databricks ML, MLflow, Unity Catalog, Workflows, and Model Serving.
- CI/CD and MLOps automation.
- Python and production ML deployment patterns.
MLOPS Engineer in London employer: Capgemini Europe
As a Microsoft Viva Architect in London, you will join a forward-thinking company that prioritises employee experience and innovation. With a strong commitment to professional development, our collaborative work culture fosters continuous learning and growth, while our focus on data-driven solutions ensures that your contributions have a meaningful impact. Enjoy the unique advantage of working in a vibrant city that is at the forefront of technology and business transformation.
