NLP/Semantic Engineer/Semantic Solution Engineer
PrivateAI is an AI protocol to store, process, validate and sell your data assets. PrivateAI will generate datasets for you from any unstructured data you provide.
About PrivateAI
PrivateAI is an AI protocol to store, process, validate and sell your data assets. It generates datasets from unstructured data, using semantic models to ensure they are machine learning ready. The PrivateAI ecosystem includes knowledge graphs for data visualization, a data marketplace for buying and selling proprietary data, and a peer-to-peer environment for researchers to share insights. It also features a platform for knowledge-intensive crowdsourcing with a dynamic reward system. The native token, $PGPT, represents the value of datasets and is used for payments and contributions. The platform is built on a privacy-by-design methodology, utilizing Fully Homomorphic Encryption (FHE), Confidential Machine Learning (ConfML), and a Tendermint-based consensus to ensure data security and privacy. Use cases span across data analytics, research labs, GenAI companies, healthcare, and predictive modeling.
Skills
About the Role
You will lead the strategy and development of enterprise semantic solutions, researching cutting-edge approaches and toolkits to solve complex problems in the semantic and ontology domain. You will design and implement semantic layer solutions such as taxonomy and ontology management tools, graph databases, triple stores, and labeled property graphs. You'll interpret existing semantic schemas, help develop solution architectures and governance plans, and ensure the quality, interoperability, and reusability of data and knowledge assets following FAIR Data Principles and 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 use of generative AI and LLMs in complex scientific domains
- Expertise in FAIR Data Principles and the Semantic Web technology stack (SHACL, RDF, RDF*, OWL, etc.) and experience using ontology development tools
- 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
- Knowledge of cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes)
- Experience with SQL and NoSQL databases
- Understanding of web technologies (HTML, CSS, JavaScript)
- Bachelor's Degree in Computer Science, Information Science, Knowledge Management, Library Science, Data Science or related field
Responsibilities
- Research state-of-the-art approaches and toolkits for solving problems related to the semantic and ontology domain
- Propose methodologies covering various text/image/graph/chart analysis challenges
- Lead the strategy, design and development of enterprise semantic solutions such as metadata, taxonomies, ontologies and knowledge graphs
- Lead the implementation of semantic layer solutions such as taxonomy/ontology management tools, graph databases/triple stores and labeled property graphs
- Interpret existing semantic schemas and help develop and deliver design and implementation of solutions architectures and governance plans
- Ensure the quality, interoperability and reusability of data and knowledge assets following FAIR Data Principles and Semantic Web standards
Benefits
- Performance-dependent bonuses including commission from funding raised
- Vesting in the form of tokens
- Access to personal networks and prestigious memberships of the company, its advisors and the CEO
- Invitations to attend conferences or business events in global tech and finance hotspots with expenses paid by the company