Staff Applied Scientist - Knowledge Graphs & AI

📋 Description Knowledge Graph Design & Construction: architect per-tenant schemas and ontology. Information Extraction: build NLP pipelines to extract knowledge from unstructured data. Contextual reasoning & recommendations: design layers for next-best-action. Representation Learning: train graph models (GNNs, embeddings) for reasoning. Domain Modeling: formalize sales concepts into structured representations. Cross-functional Collaboration: work with engineering, product, and data teams to deploy models. 🎯 Requirements PhD in CS/NLP/ML with focus on knowledge representation, reasoning, and information extraction. Strong engineering fundamentals; production-grade Python; graph DBs (Neo4j, SPARQL). Comfort with ambiguity; decompose vague goals into concrete problems. Track record delivering production systems beyond prototypes. Strong ownership from research to deployment with minimal oversight. Strong communication; mentoring or leading technical work. 🎁 Benefits Greenfield architecture: shape Halcyon Labs's AI platform. PhD-level challenges in knowledge graphs and reasoning. Applied impact: production feedback across millions of interactions. High leverage, low bureaucracy: senior team, fast shipping. Career growth: opportunities to lead initiatives and mentor. RSU program and inclusion initiatives.