1 to 25 of 35 Permanent Ontologies Jobs in London

complex, ambiguous environments. * A strategic mindset combined with the ability to drive practical outcomes. Desirable Experience * Cloud migration and cloud-native data architecture. * Ontologies, semantic modelling or knowledge graphs. * AI-enabled data architectures and emerging technologies. * Experience developing enterprise data standards and frameworks. DV Clearance Eligibility Requirements * UK residency history ...

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. ...

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 ...

programmes , from conceptual modelling through logical/physical layers, tied directly to business priorities. Develop a unified language for data -dictionaries, vocabularies, taxonomies and ontologies that allow teams to interpret data consistently. Shape data and analytics architectures collaboratively with solution and enterprise architects. Act as a trusted advisor to senior ...

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 ...

Retrieval-Augmented Generation), or conversational AI frameworks. Semantic Modeling: A solid understanding of how to map business logic to physical data (semantic layers, ontologies, or metrics layers). Programming Skills: Proficiency in Python for data manipulation and scripting; familiarity with API integrations. AI Native: Demonstrated ability to utilize AI coding ...

designing and optimising CI infrastructure. Experience with document processing pipelines – PDF parsing, OCR, structured data extraction. Familiarity with knowledge representation – decision trees, knowledge graphs, ontologies, or symbolic reasoning systems. Experience with LLM integration in production systems – prompt engineering, evaluation, working with APIs such as Gemini, Claude, or OpenAI. Frontend experience ...

Retrieval-Augmented Generation), or conversational AI frameworks.* **Semantic Modeling:** A solid understanding of how to map business logic to physical data (semantic layers, ontologies, or metrics layers).* **Programming Skills:** Proficiency in Python for data manipulation and scripting; familiarity with API integrations.* **AI Native: Demonstrated ability to utilize ai coding ...

Posted 9 months ago Tech stack SQL Python Responsibilities Design and build robust data pipelines within Foundry. Integrate diverse data sources using Foundry's Ontology and Code Workbooks ( Python , SQL). Develop and maintain Foundry applications (data lineage, pipelines, object models). Collaborate with analysts, data scientists. Compensation Competitive Role ...

primary challenge is creating and maintaining the knowledge graph that powers intelligence, discovery, and workflow automation across the platform. About You Knowledge Graph Design & Ontology Modelling : Expertise in modelling complex domains as interconnected graphs, covering companies, sponsors, lenders, law firms, financial instruments, transactions, documents, events, and their relationships. Entity Resolution ...

pipelines, workflows, and information models Develop solutions that support analytics, AI, operational applications, and decision support Contribute to the design and development of Foundry Ontologies Work within agile, multidisciplinary delivery teams across complex environments Build strong client relationships while delivering tangible outcomes Your Responsibilities: Design and implement scalable data pipelines … data governance, metadata management, data quality, and lineage Experience working with batch, streaming, real‐time, and unstructured data Strong understanding of data modelling and Ontology design Experience designing scalable data architectures and information assets Coding experience in Python, TypeScript , or similar languages Understanding of SDLC principles, version control ...

team. Design and build scalable, reliable data pipelines that ingest data from infrastructure, platform services, and business systems. Define data models, schemas, and ontology structures that support operational workflows and use cases across the business. Clean, transform, and structure data to create a digital twin of Nscale. Implement permissioning … Foundry with existing systems and data sources, ensuring seamless data flows. Profile and Required Skills Deep, hands‐on expertise in Palantir Foundry , including ontology modelling, pipeline development, data architecture, and large-scale platform design. Proven experience providing technical leadership—setting architectural direction, mentoring engineers, and defining standards in a data ...

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 ...

pivot fast in a fast‐moving environment. It would be great if you had GraphRAG Experience: Familiarity with Knowledge Graphs (e.g., Neo4j) and ontologies to enhance standard vector RAG with highly structured, interconnected corporate data. Local/Open‐Weight Model Deployment: Experience deploying and fine‐tuning open‐weight models (like ...

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 ...

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 ...

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 ...

time-series and multimodal data, simulation and world models, trustworthy decision-support agents and staged autonomy, and AI-native approaches to industrial data foundations, ontology learning, and evaluation. This is a hands‐on role for someone who thrives in uncertain problem spaces, works with high autonomy, and finds practical ways ...

Data-as-a-Service as a real product — a secure, multi-tenant, immutable release architecture, with data made discoverable at scale through catalogue and ontology-driven search, in partnership with the data team. Powering agentic AI from the data platform — scaling the data foundations behind MystraAI and owning secure, tenant ...

tune – Codify the firm's unwritten methods and judgements into the coworkers and playbooks that run at machine speed. Anchor them through the ontology and semantic layers in Celeste so the agents reason the way its own people do. Earn adoption – Lead the actions that earns Celeste's adoption, from ...

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 ...

will bridge the gap between complex biomedical data and actionable AI applications. You will conduct comprehensive health checks on our current stack, refine bio-ontologies, an... WKCL1_UKTJ ...

NIST AI RMF and enterprise governance standards Data, Semantic & Knowledge Architecture Support development of enterprise semantic and knowledge capabilities Define architecture approaches for: enterprise ontologies semantic models metadata-driven platforms knowledge graph integration unstructured data processing Ensure trusted and governed data foundations underpin AI-enabled capabilities Collaborate with data architecture … operational teams Experience influencing senior stakeholders within matrixed organisations Technical skills AI orchestration and agentic workflow architectures RAG and GraphRAG architectures Knowledge graphs, ontologies and semantic technologies Vector databases and semantic retrieval patterns Microsoft Fabric, Azure AI and modern cloud platforms API and integration architecture Enterprise security and identity models ...

technical expectations. Customer Advisory: Provide remote and on-site technical advisory services to customers, offering guidance on data attributes, integration strategies, and system optimization. Ontology & Model Development: Advise on the evolution of Janes data models and ontologies to ensure compatibility and seamless integration with customer ecosystems. Gap Analysis: Identify ...

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 ...