Knowledge Engineer | Saal.ai

About Saal.ai:

Saal.ai is a U.A.E based organization focusing on an AI framework capable of performing cognitive tasks via multimodal sensor inputs. We strive towards Artificial General Intelligence using learning paradigms such as Active Learning, Meta-Learning and Reinforcement Learning. We are committed to developing market leaders in industries we operate, and we continue to evolve our technology and business models to deliver value to our eco-system.

Position Description:

Looking for 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.

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.
  • Propose solutions and strategies to business challenges
  • Collaborate with engineering and product development teams
  • Proactively advice on best practices.
  • Good understanding of data integration, data quality and data integrity concepts.
  • Experience with graph query languages, graph query optimization, and graph data indexing and storage.
  • Good understanding of Semantic and Linked Data concepts, such as ontologies.

Qualifications:

  • Ph.D. or MS degree with industry experience as a Knowledge Engineer/Ontology engineer with at least 2 years of experience
  • 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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