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Designs, trains, evaluates, and productionizes machine learning models and AI systems using complex public-sector datasets. Builds reproducible ML pipelines, schema-aware data flows, LLM and RAG workflows, NLP models, and containerized services integrated with the OneView platform. Leads technical delivery for client projects, troubleshoots production issues, configures modeling outputs, mentors colleagues, and contributes reusable engineering components. The role is hybrid in London with occasional client travel and is a 12-month maternity leave cover.

Deliver technical client deployments of the OneView platform, including data extraction, engineering, data science, cohort development, dashboards, predictive models, and analytics. Manage technical project delivery, stakeholder communication, benefits tracking, client training, testing, and platform improvements. Work with consulting, governance, product, and QA teams to translate client data into actionable insights and measurable social impact.

The Data Engineer will build and maintain data pipelines, ensuring quality and performance while collaborating with teams to support platform evolution and product delivery.

Build and scale a predictive modeling platform supporting multiple problem types and tenants. Develop embedding-based, temporal survival, and gradient-boosted models for social-domain risk prediction. Create training datasets, evaluation pipelines, and production ML infrastructure, while researching and safely deploying emerging ML and LLM techniques. Implement containerized APIs and Kubernetes services, and incorporate responsible AI, ethical, and regulatory considerations throughout development.

Own and evolve the platform infrastructure for deployed ML and NLP systems: deploy and monitor models via Azure ML and AKS, build orchestration pipelines (Dagster), ensure observability and Responsible AI/GDPR compliance, and support scaling across multi-tenant local authority clients while advising across the organisation.