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AI Knowledge Graph Conflict Resolution Developer

Isaac Singh

Full-time · Job · New_York

About the role

A knowledge graph built from multiple sources will contain conflicts. Two news articles say the same person was born in different cities. A corporate registry says a company was founded in 2008; a Wikipedia scrape says 2009. A scientific database records a drug as approved for condition A; a regulatory filing says the approval is pending. These conflicts are a signal — they reveal data quality problems, source disagreements, or genuinely uncertain facts — but only if you can detect and surface them systematically. Our knowledge graph platform serves 28 enterprise clients in finance, healthcare, and legal sectors whose business decisions depend on the accuracy of the knowledge we maintain. Conflict detection is a critical reliability feature: before any fact in our graph is surfaced to a downstream application, we need to know whether it's unambiguously supported, contested across sources, or temporally superseded. You'll build the conflict resolution system: detecting contradictory assertions across source documents, estimating source credibility weights, implementing resolution strategies for different conflict types, and building the confidence scoring that expresses how certain we are about each contested fact. The system serves 180 million graph assertions and needs to scale.

Responsibilities

  • Build conflict detection pipeline identifying contradictory assertions across 180M knowledge graph entries
  • Implement source credibility weighting for resolution prioritization across heterogeneous data sources
  • Design resolution strategies for temporal, categorical, and numerical conflict types
  • Create confidence scoring for contested facts based on source agreement and credibility
  • Build conflict audit trail documenting resolution decisions for client inspection
  • Develop conflict resolution accuracy evaluation using domain expert annotation as ground truth

Requirements

  • 3+ years in knowledge graph engineering, information extraction, or data quality systems
  • Strong Python, SQL, and NLP skills with graph data familiarity
  • Experience with entity resolution, data fusion, or multi-source information reconciliation
  • Understanding of knowledge representation and assertion confidence modeling
  • Ability to design systems that scale to hundreds of millions of assertions

Benefits

  • Fully remote with flexible schedule
  • Health, dental, and vision insurance
  • $3,000 annual learning budget
  • 401(k) with match
  • Equity options

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Categories

Automation & AI Workflows NLP & Prompt Engineering

Skills

python pytorch hugging face sql spark

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Level

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Language

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