Senior Machine Learning Engineer (Maternity Leave Cover)

Xantura Limited is an AI-driven technology company helping local authorities use data and predictive analytics to reduce societal inequality. The Senior Machine Learning Engineer will design, train, evaluate, and productionise machine learning and AI models, build data and model pipelines, and deploy containerised services into the OneView platform. The role also involves technical delivery for clients, platform configuration, troubleshooting, mentoring, and knowledge sharing.

Responsibilities:

• Design, train and optimise predictive models using advanced architectures such as gradient boosted trees, temporal models and embedding based models
• Build robust training, evaluation and monitoring pipelines to ensure model quality, reproducibility and auditability
• Implement feature engineering, hyperparameter tuning, model debugging and performance optimisation
• Productionise models so they run reliably and efficiently at scale in client environments
• Own schema aware data flows for modelling and cohorts; validate, transform and version datasets used in training and inference
• Manage and evolve database schemas; optimise SQL, indexing and partitioning for large training and scoring workloads
• Lead the modelling and data engineering components of client projects alongside DACs and Business Consultants
• Acquire and extract data from client source systems
• Build and validate cohort logic to ensure accuracy, interpretability and alignment with client needs
• Troubleshoot and resolve complex modelling and pipeline issues throughout delivery
• Build and integrate LLM based components including embedding pipelines, RAG workflows and text analysis models
• Develop and deploy agentic and multicomponent AI systems using modern ML frameworks
• Engineer high performance NLP and sequence models for information extraction, classification and risk prediction
• Configure advanced OneView components linked to modelling outputs such as risk logic, summaries and scoring pathways
• Contribute modelling innovations, performance insights and engineering improvements back into the platform
• Act as an SME for machine learning, AI and model engineering within DACs
• Mentor DACs on Python, modelling best practice, data engineering fundamentals and debugging approaches
• Produce documentation, templates and reusable components to raise engineering standards across delivery