GHX
Healthcare
SoftwareEngineerIII-KnowledgeRepresentation(OntologyandMLEngineer)
Neural analysis suggests this role is
optimal for Mid candidates.
“Software Engineer III - Knowledge Representation (Ontology and ML Engineer) at GHX. Skills: Knowledge Representation, Ontology Design, Graph Technologies, Machine Learning, AI Solutions, Python, SQL, Cloud Computing. Maintaining GHX’s position at the forefront of AI solutions in Healthcare. Applying modern methods for knowledge representation including ontology creation”
What You'll Achieve.
Assure correct and complete information; Support explainability and transparency; Solidify GHX's role as the leader in AI in the Healthcare Supply Chain
Industry & Context.
Translate needs and challenges into solutions; Modular problem decomposition
What They're Looking For.
Must Have
Greater than 3 years working as a software engineer or data scientist, Expertise with one or more Graph query languages (SPARQL, Cypher, Gremlin) and the associated Graph Databases, Experience with Tabular (SQL), Document (NoSQL), and Vector/Semantic databases and their interactions with Graph DBs, Expertise with Python & SQL, Experience with AWS cloud resources (S3, EC2, ECS, Lambda), Experience with Docker or other container services, Specification and creation of APIs and microservices
Nice to Have
Computer Science or hard sciences Bachelors degree, Passion to stay on the cutting edge in knowledge representation solutions, Experience with Generative AI solutions, Sense of humor
What You'll Do.
Maintaining GHX’s position at the forefront of AI solutions in Healthcare
Applying modern methods for knowledge representation including ontology creation
designing and curating key ontological structures in the Health Care Supply Chain
document and vector store capabilities
Designing and implementing ontology and graphical structures
Integrating graph solutions with other data stores and technologies
Leveraging LLMs/GenAI and rules engines for data I/O and data curation
Handling multimodal data
Developing and maintaining software tools to support knowledge representation needs
Implementing tools for evaluating and monitoring solution performance
Inventing and deploying novel solutions with maintainable APIs
How You'll Work.
Team & Collaboration
Collaborate with internal and external stakeholders including users, developers, product managers, leadership, etc.; Join a team that is tasked with leading GHX through a transformational change
Full Job Description
The Software Engineer 3 focusing on Knowledge Representation will play a key role in maintaining GHX’s position at the forefront of AI solutions in Healthcare. This role will be responsible for applying modern methods for knowledge representation including ontology creation that interact with intelligent systems to meet the challenges GHX faces in assuring affordable quality healthcare for all. This Engineer will define, design and curate the key ontological structures needed in the Health Care Supply Chain using data driven, ML and agentic approaches. They will leverage graph, table, document and vector store capabilities that interact with AI solutions and make sense of diverse internal and external data. This is a key strategic role in GHX’s AI strategy, assuring correct and complete information while supporting explainability and transparency. The role will primarily be focused on the design and implementation of ontology and graphical structures that interact with other data stores as well as AI solutions including generative and rule based. They will join a team that is tasked with leading GHX through a transformational change and solidifying its role as the leader in AI in the Healthcare Supply Chain. Essential Duties: Collaborate with internal and external stakeholders including users, developers, product managers, leadership, etc., to understand needs and challenges and translate these into solutions. Design & develop scalable structures and databases to capture, store and query structured, semi-structured and unstructured data. Design and maintain ontologies and data architectures to represent complex relationships and entities. Integrate graph solutions with other data stores and technologies. Leverage LLMs/GenAI and rules engines for data I/O and data curation. Multimodal data handling: incorporate text, images, videos, tables, graphs, rules, etc., into the knowledge representation system. Proactively explore new techniques and emerging trends to drive a
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