2 of 2 Domain Models Jobs in Lancashire

capabilities. Retrieval-Augmented Generation (RAG): Implement, optimise, and scale RAG pipelines for effective information retrieval from structured and unstructured sources. Model Fine-Tuning & Training : Train domain-specific models using techniques like LoRA, QLoRA, PEFT, reinforcement learning, and supervised fine-tuning (SFT). Model Deployment & Inferencing : Optimise model serving and inference using vLLM, DeepSpeed, TensorRT, Triton, and other … End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. Full-Stack Integration : Develop APIs and integrate ML models into web applications using FastAPI, Flask, React, TypeScript, and Node.js. Vector Databases & Search : Implement embeddings and retrieval mechanisms using Pinecone, Weaviate, FAISS, Milvus, ChromaDB, or OpenSearch. Required skills & experience More ❯

the roadmap. Technical Leadership Design, optimize, and govern modern, large-scale data architectures. Oversee architecture across applications, infrastructure, and ecosystem integrations. Apply advanced performance tuning, database optimization, and domain-driven design principles. Collaborate with and mentor engineers on system architecture, CI/CD workflows, and API integrations. Provide technical oversight in data modeling, system scaling, availability, and reliability. … SQL Server, including: Database design and performance tuning Transact-SQL (T-SQL), C# REST API integration Familiarity with Data Lakehouse architectures, especially Databricks. Strong understanding of data architecture, domain modeling, and system design in distributed environments. Experience working in Agile environments with cross-functional teams. Proficiency in workflow optimization through tooling, process, automation, and AI augmentation (including Agentic … AI). Domain knowledge in IT Asset Management, FinOps, or vulnerability intelligence is a plus. Personal Attributes Clear communicator: Crisp, honest, and transparent communication style. Data-driven mindset: Always seeks to validate hypotheses with data. Detail-oriented and strategic: Able to zoom into details while maintaining a broader perspective. Hands-on leader: Actively seeks challenges and empowers the More ❯