AI Semantic Role Labeling Model Developer

About the role

Responsibilities

• Fine-tune SRL models on financial and legal event corpora where general-domain models perform poorly
• Build domain-specific frame definitions for regulatory, transactional, and legal event types
• Implement high-throughput SRL serving integrated with the existing NLP document processing pipeline
• Develop event-to-knowledge-graph mapping converting SRL output into structured entity-relation-event triples
• Create SRL quality evaluation framework benchmarking against expert-annotated domain event extractions
• Handle cross-sentence event coreference tracking events that span multiple sentences in long documents

Requirements

• 6+ years in NLP engineering with semantic parsing, information extraction, or structured prediction experience
• Deep understanding of semantic role labeling frameworks: PropBank, FrameNet, and domain-specific frame adaptation
• Strong Python and PyTorch skills with span-based extraction model development and fine-tuning
• Experience processing financial or legal text with domain-specific event structure
• Track record integrating structured NLP outputs into knowledge representation systems

Benefits

• Hybrid: 2 days NYC, 3 days remote
• Comprehensive health benefits
• $4,000 annual professional development budget
• Equity participation
• Bonus tied to knowledge graph completeness improvements

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