About this role
The Machine Learning Engineer role sits within Client Delivery, embedded in the Data & Analytics Consulting (DACs) team. A technical, client‑facing group of Data Scientists and ML Engineers responsible for building and operationalising advanced machine learning and AI This is a 12 months contract with potential to become a perm role afterwards.
- Machine learning and AI engineering Design, train and optimise predictive models (gradient boosted trees, temporal and embedding-based models), with reproducible training, evaluation and monitoring pipelines.
- Productionise models to run reliably at scale in client environments.
- Build and integrate LLM components (embedding pipelines, RAG, agentic systems) and NLP models for extraction, classification and risk prediction.
- Data engineering Own versioned, validated data flows for modelling and inference, including schema design and SQL optimisation for large training and scoring workloads.
- Extract data from client source systems and build cohort logic that is accurate and interpretable.
- Technical delivery Lead the modelling and data engineering components of client projects alongside DACs and Business Consultants, resolving complex modelling and pipeline issues.
- Configure OneView components linked to modelling outputs (risk logic, summaries, scoring pathways) and feed engineering improvements back into the platform.
- Knowledge sharing and technical leadership Act as SME for machine learning and AI within DACs.
- Mentor DACs on Python, modelling practice and debugging.
- Produce documentation, templates and reusable components that raise delivery standards.