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Knowledge Graph Engineer — Pharmaceutical Research
Olga Smirnova
Full-time · Senior
About the role
We're a pharmaceutical AI company. We build knowledge graphs connecting drugs, targets, diseases, clinical trials, patents and scientific literature — and our ML models reason over these graphs to surface drug repurposing opportunities and adverse event signals.
We need a knowledge graph engineer to improve our entity resolution pipeline (linking the same entity across different data sources is harder than it sounds in pharma), extend our ontology to cover new domains, and build graph-based features for our ML models.
If you know what PubChem, ChEMBL and ClinicalTrials.gov contain and why they're hard to join, this role is probably for you.
Requirements
- – Graph database experience (Neo4j or similar)
- – NLP for entity extraction and resolution
- – Familiarity with biomedical ontologies (MeSH, SNOMED, ChEBI)
- – Python for ETL and graph construction
- – Comfortable working in a domain with deep expert feedback (our team includes PhDs in biochemistry)
Job Type
Full-time
Level
Senior
Language
English
Salary Range
$120k – $160k / year
AI Expertise
AI & Machine Learning Engineers
NLP & Prompt Engineering
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