Drive innovation in Document Understanding at Thomson Reuters as a Senior Applied Scientist. Your work will directly support renowned products like Westlaw and PracticalLaw.
This role involves designing and deploying cutting-edge document understanding systems, focusing on semantic chunking, information extraction, and knowledge graph construction. You will collaborate with engineering and product teams to deliver scalable solutions that enhance legal content processing. Candidates should possess experience in production systems and a background in LLM methodologies.
Key Responsibilities:
• Design and deploy semantic chunking models for legal text
• Build systems for classifying and enriching documents
• Develop pipelines for knowledge graph extraction
• Create systems for synthetic data generation solutions
• Implement evaluation frameworks for system performance
Requirements:
• PhD or Master’s in Computer Science or related fields
• 5+ years in industry-focused document understanding
• Track record of publications in leading AI conferences
• Expert in Python and Deep Learning frameworks
• Experienced in document analysis and extraction methods
Channel your skills to advance legal AI and transform Document Understanding at Thomson Reuters.
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