Job Purpose

A hands-on Knowledge engineer who is passionate about applying Semantic Technologies, NLP techniques to solve real world problems which will make a lasting impact on society. You will work closely with the wider team to ensure high-quality algorithm is delivered in line with the project goals and delivery cycles. You will work on all aspects of the design development and delivery of AI enabled solution including planning, developing, feature development, accuracy improvement, project maintenance, and language-targeted research for improvements and maintaining high-quality applications.

 



Key Responsibilities

Expand the capability of our knowledge graph building and to incorporate the latest research ideas.

Design and implementation of knowledge graph starting from structured and unstructured resources.

Knowledge graph reasoning and inferences.

  • Good understanding of Semantic and Linked Data concepts, such as ontologies.
  • Experience with graph query languages, graph query optimization, and graph data indexing and storage.
  • Good understanding of data integration, data quality and data integrity concepts.

Propose solutions and strategies to business challenges

Collaborate with engineering and product development teams

Proactively advice on best practices.

 

 

 

Education, Experience and Required Skills

Ph.D. or MS degree with industry experience as a Knowledge Engineer/Ontology engineer

 

Minimum 2 years

 

 

Essential Skills

Experience in NLP.

Experience with large volumes of information

Knowledge of machine learning algorithms and data mining techniques.

Experience in large scale knowledge graphs

Familiarity with Ontology Learning and Ontology Engineering.

  • Hands on experience with graph databases or RDF stores (Neo4j, OrientDB, Jaunus Graph, etc.)

Demonstrated experience with OWL, RDF, Ontology Repositories, SPARQL and Semantic Services is a plus

Great organizational skills with the ability to thrive in a demanding environment whilst juggling multiple priorities

Collaborate with a cross-functional team including data scientists and software engineers.

Knowledge of the most important libraries for NLP.

Programming skills e.g. Python, Java.

Excellent communication skills.

 

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