Cyberhill Partners, LLC AI/ML Software Engineer – Knowledge Graphs & Ontologies Austin, TX · Remote · Full time Company website

Apply for AI/ML Software Engineer – Knowledge Graphs & Ontologies

About the Role:

We’re seeking an experienced AI/ML Software Engineer with expertise in Knowledge Graphs and Ontologies to help design and scale intelligent systems that model, reason over, and derive insights from complex structured knowledge. In this role, you'll bridge cutting-edge machine learning with symbolic reasoning, helping to build systems that understand and represent domain knowledge in a form usable by machines and humans alike.

You’ll work alongside a multidisciplinary team of engineers, data scientists, and ontologists to develop a scalable, semantically rich data infrastructure that powers search, recommendations, analytics, and automated decision-making.

Responsibilities:

• Design and implement scalable knowledge graph pipelines using ontologies, entity resolution, and relation extraction techniques.
• Integrate structured (e.g., databases) and unstructured data (e.g., text) into cohesive knowledge representations.
• Develop tools and services for knowledge ingestion, enrichment, reasoning, and querying (e.g., via SPARQL, Cypher).
• Apply machine learning and NLP techniques to extract, disambiguate, and classify entities and relationships from large datasets.
• Collaborate with ontology engineers to develop and extend domain ontologies using OWL, RDF, or SKOS.
• Build APIs and systems that expose knowledge graph capabilities to downstream applications.
• Optimize knowledge graph performance and scalability in distributed environments.
• Stay current with developments in symbolic AI, hybrid AI (neuro-symbolic), and graph-based ML.

Basic Qualifications:

• Bachelor’s or Master’s in Computer Science, AI, Semantic Technologies, or related field.
• 3+ years of experience in software engineering with AI/ML applications.
• Hands-on experience with knowledge graph technologies (e.g., RDF, OWL, SPARQL, Neo4j, TigerGraph).
• Experience with NLP and ML tools (e.g., spaCy, Hugging Face, Scikit-learn, PyTorch, TensorFlow).
• Proficiency in Python (or similar languages) and familiarity with software development best practices.
• Understanding of ontological modeling and reasoning principles.
• Experience building and deploying production-grade ML systems or graph pipelines.

Preferred Qualifications:

• Experience working with large-scale graph databases or triple stores.
• Familiarity with standards like W3C Semantic Web stack, SHACL, and schema.org.
• Knowledge of probabilistic reasoning, embeddings for graphs (e.g., node2vec, TransE), or GNNs.
• Experience in domain-specific knowledge modeling (e.g., healthcare, finance, scientific research).
• Familiarity with hybrid symbolic-neural architectures.

What We Offer:

• Competitive salary with equity options
• Flexible remote work environment
• Comprehensive benefits including health, vision, and dental
• An opportunity to work at the forefront of AI and knowledge systems
• Learning and development support for ongoing career growth