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Machine Learning Engineer
X4 Technology
- London, England, United Kingdom
- London, England, United Kingdom
Über
Databricks-focused
Machine Learning Engineer for a 12-24 month contract.
This role supports the full end-to-end model lifecycle in production environments built on Azure and Databricks, collaborating with business units, customer teams across international business units.
Databricks expertise is a must.
Core Responsibilities
Build and manage ML/MLOps pipelines using Databricks.
Design, optimise and operate robust end‑to‑end machine learning pipelines within the Databricks environment on Azure.
Support internal project teams and act as a technical point of contact for onboarding to Databricks, model deployment and pipeline design.
Leverage key Databricks features such as MLflow, Workflows, Unity Catalog, Model Serving and Monitoring to enable scalable and manageable solutions.
Implement governance and observability, integrating compliance, monitoring and audit features across the full machine learning lifecycle.
Lead efforts to move models into production, ensuring they are stable, secure and scalable.
Work directly on model hosting, monitoring, drift detection and retraining processes.
Collaborate with teams in customer‑facing meetings, workshops and solution design sessions across departments.
Contribute to platform and knowledge improvement, supporting continuous development of Databricks platform services and promoting knowledge sharing across teams.
Essential Skills and Experience
End‑to‑end ML/AI lifecycle expertise with hands‑on experience across data preparation, model development, deployment, monitoring and retraining.
Proficiency with Azure Databricks and core components: MLflow, Delta Lake, Unity Catalog, Workflows, Model Serving.
Experience with machine learning frameworks (PyTorch, TensorFlow, or Scikit‑learn).
DevOps and automation knowledge: CI/CD pipelines, infrastructure‑as‑code (e.g., Terraform), container technologies like Docker.
Cloud platform familiarity, preferably Azure, with openness to AWS or other providers.
Strong stakeholder‑focused communication, explaining complex technical concepts clearly.
Governance and compliance awareness, including explainability and security controls.
Experience with large language models, generative AI or multimodal orchestration tools (optional but plus).
Familiarity with explainability libraries such as SHAP or LIME.
Previous use of Azure services such as Azure Data Factory, Synapse Analytics or Azure DevOps.
Background in regulated industries such as insurance, financial services or healthcare (plus).
If this sounds like an exciting opportunity, please apply with your CV.
Seniority level
Mid‑Senior level
Employment type
Contract
Job function
Information Technology
Business Consulting and Services
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Sprachkenntnisse
- English
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