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 Outreach'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.