About the company
We are an early-stage (Seed secured) Crypto AI startup that aims to monetize scientific research, datasets and other kinds of IP through marketplaces tailored to AI companies that seek to acquire quality data for training. Our platform offers ways to participate in the AI economy without compromising the data, keeping it private (hence PrivateAI). All our co-founders have previously founded and exited multiple crypto unicorns ($AGIX, $SYS, $DOGE, $FTM)
About the Role
We are looking for a Semantic Solution Engineer who will be leading the process of working on semantic solutions to complex problems, developing metadata, taxonomies, ontologies and knowledge graphs to organize and unify information, and leveraging inference to make sense of large quantities of data, answering practical questions and uncovering unexpected connections, the person who can contribute value to the creation of semantic technology applications and semantic models by utilizing cutting-edge hybrid techniques.
Responsibilities
- Research state-of-the art approaches and toolkits for solving problems related to semantic and ontology domain.
- Propose methodologies covering various text/image/graph/chart analysis challenges.
- Lead the strategy, design and development of enterprise semantic solutions (metadata, taxonomies, ontologies, knowledge graphs, etc.).
- Lead the implementation of semantic layer solutions, such as taxonomy/ontology management tools, graph databases/triple stores, labeled property graphs (LPGs), etc.
- Interpret existing semantic schemas and help to develop and deliver the design and implementation of solutions architectures and governance plans.
- Play a key role in ensuring the quality, interoperability, and reusability of our data and knowledge assets, following the FAIR Data Principles and the Semantic Web standards.
Requirements
- At least 3 years designing and managing taxonomies, thesauri, and/or ontologies.
- Expertise in knowledge engineering, knowledge representation, ontology development, and in the use of generative AI and LLMs in complex scientific domains.
- Expertise in the FAIR Data Principles, the Semantic Web technology stack (SCHACL, RDF, RDF*, OWL, etc.), and experience using ontology development tools .
- Driven by a strong belief in the business applications of knowledge graphs and ability to adapt to new technology.
- Experience using semantic standards like RDF, OWL, SKOS, and SPARQL.
- Programming experience (e.g., Java, C/C++, Python).
- Experience/knowledge in data modeling, NLP, pattern recognition, knowledge graphs.
- Experience in natural language processing tools and platforms (such as spaCy) and computational linguistics will be considered as a strong advantage.
- Knowledge of cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Experience with SQL and NoSQL databases.
- Understanding of web technologies (HTML, CSS, JavaScript).
- Education:some text
- Bachelor’s Degree in Computer Science, Information Science, Knowledge Management, Library Science, Data Science or related field.
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