17 of 17 SPARQL Jobs

applications. Solid understanding of Object-Oriented Design and Design Patterns. Experience implementing the Marklogic Java-client-API within an enterprise application. Strong knowledge of XQuery, FLWOR queries, JavaScript, Marklogic, SPARQL, RDF data, XML Data, triple-stores, and XML Processing. Experience developing Marklogic Entity Models and building Marklogic data hubs. Proficiency with Unix/Shell scripting. In-depth experience with Java More ❯

Graph Expertise: You understand the value of nodes, edges, and properties - and how to model them effectively. Query Proficiency: Hands-on experience with graph query languages like Cypher, Gremlin, SPARQL, or GraphQL. Data Modeling: You know how to translate domain knowledge into graph schemas that support performant queries and analytics. Algorithm Knowledge: You've implemented graph algorithms like shortest path More ❯

and relationship patterns essential for effective graph database design Graph Query Language Proficiency: Demonstrated expertise in one or more graph query languages such as Cypher (Neo4j), Gremlin (Apache TinkerPop), SPARQL, or GraphQL for complex data retrieval and manipulation Advanced Graph Data Modeling: Experience translating business requirements into optimized graph schemas, including property graphs, RDF triples, or knowledge graph ontologies Graph More ❯

Familiarity with Hume or similar graph intelligence platforms is a plus Comfortable working in agile and data-driven teams Desirable: Exposure to linked data or semantic web technologies (RDF, SPARQL) Background in intelligence, law enforcement, government, or fraud analytics Experience working on sensitive or classified data projects Additional Details: Inside IR35 Initial 6-month contract with potential extension Start ASAP More ❯

mock-up tools such as Figma Exposure to cloud technologies (. AWS) Exposure to Golang Exposure to logic programming – Rego, Datalog or Prolog Exposure to RDF technologies such as SparQL or JSON-LD #J-18808-Ljbffr More ❯

directly impact customers. OUR TECHNOLOGY STACK: Python • Agentic tools (Autogen, Semantic Kernel, LangChain) • SQL • MongoDB • Third-party LLM APIs • LiteLLM • MLflow • Google Cloud Platform • Docker • PyTorch • Hugging Face Transformers • SPARQL • Kubernetes WHAT YOU WILL BE DOING AT BEAMERY Join us at the forefront of transforming how organisations manage talent and plan their workforce. We're building intelligent products powered by More ❯

mock-up tools such as Figma Exposure to cloud technologies (e.g. AWS) Exposure to Golang Exposure to logic programming - Rego, Datalog or Prolog Exposure to RDF technologies such as SparQL or JSON-LD About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and More ❯

to make informed design and code decisions. Database Management Work with relational databases (RDBMS) and the graph database RDFox Write and optimize complex SQL queries Use RDF models and SPARQL queries from the graph database along with our Ontology expert DevOps and CI/CD Participate in the CI/CD pipeline using GitLab Utilize tools to improve coding style More ❯

pros and cons for informed decision-making Database Management Work with relational databases (RDBMS) and the graph database RDFox Write and optimize complex SQL queries Use RDF models and SPARQL queries from the graph database in collaboration with our Ontology expert DevOps and CI/CD Participate in the CI/CD pipeline using GitLab Utilize tools to improve coding More ❯

to make informed design and code decisions. Database Management Work with relational databases (RDBMS) and the graph database RDFox. Write and optimize complex SQL queries. Use RDF models and SPARQL queries from the graph database in collaboration with our Ontology expert. DevOps and CI/CD Participate in CI/CD pipeline using GitLab. Containerize applications using Docker. Work with More ❯

formal test methods, deterministic simulation testing, Satisfiability Modulo theories,Boolean Satisfiability Experience with declarative model transformations or mappings – e.g. in a data pipeline Exposure to RDF technologies such as SparQL or JSON-LD #J-18808-Ljbffr More ❯

or cloud-based either as Software-as-a-Service (SaaS) or hosted Ideally hands-on knowledge of graph technologies such as RDF, LPG and ontologies (OWL). Experience with SPARQL a bonus Familiarity with Large Language Models, and leveraging LLMs in a corporate environment to drive business value Experience selling to or working within the data management and/or More ❯

technologies and cloud platforms. Exposure to graph libraries, mock-up tools like Figma, and cloud services such as AWS. Familiarity with Golang, logic programming (Rego, Datalog, Prolog), RDF technologies (SPARQL, JSON-LD). About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to prominent clients worldwide. We value diversity and are committed to More ❯

formal test methods, deterministic simulation testing, Satisfiability Modulo theories, Boolean Satisfiability Experience with declarative model transformations or mappings - e.g. in a data pipeline Exposure to RDF technologies such as SparQL or JSON-LD About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and More ❯

learning, knowledge engineering, information retrieval, or related fields. At least 3 years of work experience in at least one of the following fields is REQUIRED: Knowledge engineering technologies (RDF, SPARQL, OWL, SKOS)/Natural Language Processing (LLM, agent, entity detection, question answering, etc.)/Machine Learning & Deep Learning (LSTM, transformer, etc.) . At least 2 (3-5 would be desirable More ❯

and support product scaling initiatives Key Requirements: PhD in NLP, Machine Learning, Knowledge Engineering, or related fields 3+ years of experience in at least one of: Knowledge technologies (RDF, SPARQL, OWL, SKOS); NLP (LLMs, entity detection, question answering, agent systems); Deep learning (transformers, LSTM, etc.) 2+ publications in top-tier conferences (e.g., ACL, NeurIPS, ICML, EMNLP, ICLR, AAAI) Strong coding … research and applied development in a collaborative environment Keywords: Knowledge Graphs/LLMs/Semantic Search/Knowledge Reasoning/NLP/Agent Systems/RAG/OWL/SPARQL/Transformers/Deep Learning/AI Assistants/QA Systems/Pytorch/TensorFlow/Graph Reasoning/Multi-Modal AI/Knowledge Engineering/Research to Production If More ❯

successful leading and mentoring teams in a large cross domain environment or through a transformational organizational change. Expertise in knowledge representation syntax (e.g., OWL, RDF, SKOS), query languages (e.g., SPARQL), and tools (e.g., Protégé, TopBraid, PoolParty). We'd love to see: Understanding of Data Governance and Data Management, supported by industry certifications (e.g. DAMA CDMP, DCAM, etc.) Master's More ❯