1 to 25 of 31 Ontologies Jobs in England

Quality, Data Validation. AWS Cloud Platform, S3, IAM, CI/CD concepts, DevOps principles, Agile Delivery. Advantageous Skills: Databricks, Palantir Foundry, Foundry Pipeline Builder, Ontology concepts, Delta Lake, Secure Data Environment (SDE) experience, NHS/Healthcare data experience. Government/(url removed)/Public Sector domain experience strongly preferred. Must ...

Generative AI. Proven expertise in RAG/GraphRAG pipeline development and evaluation, including advanced retriever-reranker techniques. Experience in building knowledge bases and ontologies is highly desirable. Extensive experience in defining and implementing evaluation metrics for GenAI systems such as Recall, Precision, NDCG, LLM-as-a-Judge, BERTScore, BLEU score ...

health sector. Required Skills Strong hands-on Palantir Foundry experience Experience with healthcare datasets and interoperability standards (FHIR/HL7) Enterprise data modelling and ontology design expertise Experience in NHS, healthcare, or regulated environments Strong stakeholder communication skills Desirable AWS cloud experience DevOps/CI/CD/IaC knowledge ...

qualification. Right to work in the UK. Nice to have Experience in one or more of our domains (assessment/psychometrics, workforce skills/ontologies, recommendations, fraud detection). Familiarity with MLOps practices (CI/CD for ML, experiment tracking, data/version control) in a cloud environment. ...

business audiences Experience working independently within secure, fast-paced delivery environments DESIRABLE EXPERIENCE AWS or cloud data migration experience Knowledge of data catalogues, ontologies, or enterprise architecture frameworks (e.g. TOGAF) Experience with data lakes, data warehouses, or modern data platforms Familiarity with tools such as Visio, Sparx Enterprise Architect ...

senior data engineering, knowledge engineering or a closely related field. Experience designing scalable knowledge systems for AI-powered applications. Strong understanding of domain modelling, ontology design and information architecture. Hands-on experience with hybrid retrieval techniques, semantic search, embeddings and vector databases. Experience building reliable data pipelines and integrating multiple ...

evidence-grounded insight generation. Build intelligent retrieval, ranking, recommendation, and decision-support capabilities using modern orchestration frameworks and AI techniques. Integrate scientific metadata, ontologies, taxonomies, and knowledge assets into scalable AI workflows. Establish robust evaluation, experimentation, and monitoring frameworks to ensure quality, trust, performance, and reliability. Write production-ready Python ...

discovery, knowledge extraction, decision support, and intelligent content understanding. Work with large-scale, complex, and heterogeneous data, including scientific publications, research datasets, knowledge graphs, ontologies, taxonomies, citations, metadata, and content from every scientific discipline. Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature ...

Experience building evaluation systems for LLM-powered applications and AI assistants. Familiarity with scientific, biomedical, or scholarly datasets and workflows. Experience with knowledge graphs, ontologies, or semantic enrichment systems. Exposure to production ML systems, MLOps, and AI governance practices. Publications or applied research contributions in NLP, IR, search, recommendation systems ...

data manipulation, transformation, and pipeline development within Palantir Foundry, ensuring high performance and scalability across various data flows. Experience in data modelling and ontology development: Proven expertise in using Palantir Foundry's ontology to model data in ways that optimise its accessibility and usability, supporting robust reporting, analytics, and machine … working within Palantir Foundry's platform, leveraging its comprehensive suite of tools, including Code Workbooks, Pipelines, Object Explorer, and Foundry's data governance and ontology capabilities. Experience in multi-cloud and data migration environments: Experience working with data environments in Microsoft Asure, AWS, and legacy systems, and a proven ability ...

world's most advanced data platforms. Key Responsibilities Lead end-to-end architecture of Palantir Foundry, covering data integration, pipelines, transformations, ontology modelling, governance, and operational applications Own and evolve the enterprise ontology , defining object types, links, actions, and semantic relationships across clinical and operational domains Design scalable, modular … pipelines , following Foundry best practices (DRY principles, no circular dependencies) Integrate structured, unstructured, streaming, and IoT/device datasets using Foundry ingestion frameworks Deliver ontology-driven data products , including: KPIs and analytics frameworks Data marts Clinical pathway and care coordination insights Workforce planning and command centre capabilities Implement robust data ...

approaches to scientific research and information management. Experience or exposure to NLP, machine learning, or scientific data analysis would be advantageous. Familiarity with metadata, ontologies, or knowledge graphs would be beneficial. To Apply Please click and submit your profile and/or to discuss further, contact Theo Charles on (phone ...

will: Own large areas of platform end to end, driving components from design through to production deployment. Work on knowledge representation systems, including ontologies and knowledge graphs, to support structured reasoning over enterprise data. Design and implement RAG pipelines, including chunking, embedding, indexing, retrieval, and reranking. Build and maintain integrations ...

equivilent working experinece Basic programming skills Excellent analytical skills Experience with NLP, machine learning, or scientific data would be an advantage Familiarity with metadata, ontologies, or knowledge graphs Company: Our client is a global biopharmaceutical company focused on creating value for people living with severe diseases in immunology and neurology ...

Graph-structured data, designing and utilising relational and graph databases, and knowledge of graph algorithms. Desirable Knowledge, Skills and Experience: Familiarity with knowledge representation, ontology design and semantic or LLM based reasoning Experience with one or more graph machine learning packages (PyTorch-Geometric, PyKeen etc.) and knowledge graph toolkits (Neo4j ...

high‐throughput, low‐latency inferencing and classical ML deployment within unified, production‐ready platforms Own the architecture of the enterprise context layer—knowledge graphs, ontologies, vector search, and semantic retrieval—grounding the solution in client knowledge Set the design direction for context assembly and memory that manages prompts, context windows ...

Role Purpose: Design enterprise Context Knowledge Base capabilities enabling retrieval, reasoning and contextual intelligence. Key Responsibilities: Design RAG architecture; define taxonomy and ontology models; implement retrieval and ranking strategies; establish content governance and access controls; enable runtime context assembly. Key Skills: Context Engineering, RAG, Knowledge Graphs, Vector Databases, Semantic Search ...

Knowledge Graph Lead to shape scalable AI and KG solutions, translating real-world problems into graph-powered data architectures. You’ll guide teams, design ontologies, and drive end-to-end delivery across business and tech units. Ideal candidates bring deep KG expertise, ML model experience, and a track record ...

Modelling Integrate semantic layers with business glossaries, data catalogues, and lineage tooling Design and maintain semantic models to support agentic-AI capabilities Help develop ontologies, taxonomies, and controlled vocabularies underpinning enterprise metadata and search Define semantic modelling standards and patterns to ensure consistent meaning, interoperability, and AI readiness across data … Good Python skills, API integration, automation Practical Snowflake and Databricks experience including Cortex AI and Genie Working knowledge of OWL, RDF, SPARQL and enterprise ontology design Experience with at least one agentic AI framework GitHub Copilot or equivalent AI coding assistant experience in a professional setting Financial services background preferred ...

architecture to build. What You’ll Do Knowledge Architecture & Semantic Infrastructure. Design and own the enterprise knowledge layer—the governed semantic models, ontologies, and knowledge graph structures that ground both human analytics and AI agents in a single source of truth. Define how business meaning flows from glossaries through data … business context are prerequisites for accurate conversational analytics—not afterthoughts. Knowledge Graphs & Advanced Data Models. Hands‐on experience with graph databases, knowledge graphs, or ontology‐driven data architectures. Understanding of how graph structures enable multi‐hop reasoning, entity resolution, and context grounding for AI agents. Experience with at least ...

fund data for one of the world's largest asset managers. You will encode business rules, regulatory constraints, and identifier relationships as machine-readable ontologies — directly eliminating manual fund data processes and enabling automated validation across thousands of funds in 6 global markets. Defined POC scope, executive sponsorship, and weekly … technical guidance from two of the most recognized knowledge graph practitioners in financial services. What You'll Deliver (POC Scope) An investment fund ontology (OWL 2/RDF/Linked Data) modeling the product hierarchy: Fund > ShareClass > Listing > Security, with 73+ identifier types (ISIN, SEDOL, CUSIP, LEI, Bloomberg, and more ...

engineers, architects, and UI designers on end‐to‐end projects. You will stay current with knowledge engineering, generative AI, LLMs, and agentic systems, designing ontologies, articulating business value, and contributing to client workstreams while #J-18808-Ljbffr ...

LLMs, retrieval‐augmented generation (including hybrid retrieval across semantic, graph and keyword search, with reranking and embedding‐model selection), knowledge bases, knowledge graphs and ontologies, agentic workflows and skills, evaluation methods (eval harnesses, LLM‐as‐judge, groundedness and faithfulness metrics, tracing), and model risk controls. Experience building secure, scalable … closely with subject matter experts to refine AI tools iteratively and turn specialist feedback into practical product improvements. Strong grasp of structured data, taxonomies, ontology‐style data models and mappings across complex standards or schemas. Experience with user testing, controlled pilots, adoption planning, training and feedback loops for specialist user ...

engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with … degree or equivalent, plus at least 3 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Expertise in designing and developing KG solutions and graph‐based ML models (functional + technical) Experience with end‐to‐end data pipeline ...

remain at the forefront and drive innovation by applying these techniques to new business problems, use cases, and scenarios. You design, evaluate, and maintain ontologies, and establish the standards others follow. You justify the value to business and technology stakeholders, and construct the methodologies and data architectures that demonstrate it. … degree or equivalent, plus at least 4 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Expertise in designing and developing KG solutions and graph‐based ML models (functional + technical) Experience with end‐to‐end data pipeline ...