GHX

Healthcare

SrSoftwareEngineer-KnowledgeRepresentation(OntologyandMLEngineer)

$145–210k ~AI est. United States Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Sr Software Engineer - Knowledge Representation (Ontology and ML Engineer) at GHX. Skills: Knowledge Representation, Ontology, Graph Databases, Machine Learning. Collaborate with stakeholders. Understand needs and challenges”

Industry & Context.

Healthcare
Problems you'll solve

Modular problem decomposition; Multiple solution integration

What They're Looking For.

Must Have

8 years software engineer or data scientist, 6 years with Master's degree, Expertise with SPARQL, Cypher, or Gremlin, Expertise with Python & SQL, Experience with AWS cloud resources, Experience with Docker or container services, Specification and creation of APIs, Specification and creation of microservices

Nice to Have

Computer Science or hard sciences Bachelors degree, Experience with Generative AI solutions

What You'll Do.

Collaborate with stakeholders

Understand needs and challenges

Translate needs into solutions

Design scalable structures

Develop scalable structures

Capture structured data

Store structured data

Query structured data

Capture semi-structured data

Store semi-structured data

Query semi-structured data

Capture unstructured data

Store unstructured data

Query unstructured data

Represent complex relationships

Represent complex entities

Mentor junior engineers

Integrate graph solutions

Leverage rules engines

Handle multimodal data

Incorporate text data

Incorporate image data

Incorporate video data

Incorporate table data

Incorporate graph data

Incorporate rule data

Explore new techniques

Drive adoption of solutions

Develop software tools

Maintain software tools

Implement evaluation tools

Implement monitoring tools

Invent novel solutions

Deploy novel solutions

Create maintainable APIs

Adhere to software engineering practices

How You'll Work.

Team & Collaboration

Internal and external stakeholders; Users; Developers; Product managers; Leadership

Process & Methodology

SDLC

Full Job Description

The Sr Software Engineer 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. Lead, design & develop scalable structures and databases to capture, store and query structured, semi-structured and unstructured data. Lead, design and maintain ontologies and data architectures to represent complex relationships and entities. Mentor junior engineers. 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 tec

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