Lead Applied Scientist, Document Understanding

As Lead Applied Scientist, you will advance document understanding across legal, tax, and accounting content, building scalable AI systems that power search, reasoning, and generative experiences. You’ll shape semantic chunking, enrichment, classification, and knowledge graph work that inform multiple product teams and production workflows. The role combines research rigor with production impact, enabling millions of professionals to analyze complex documents. You’ll lead technical decisions and mentor others while collaborating across engineering to deliver reliable, scalable AI capabilities.

• hybrid work model
• flexible work arrangements
• growth and development opportunities
• comprehensive benefits
• Mental Health Days
• Headspace app access

• Design and deploy semantic chunking for lengthy, structured/unstructured legal, tax, and accounting documents
• Build document enrichment pipelines to identify types, jurisdictions, concepts, entities, and domain metadata
• Develop hierarchical and multi-label classification using standard and customer taxonomies
• Create LLM-based and traditional NLP information extraction pipelines for entities, relationships, citations, and concepts
• Develop knowledge graph construction systems to extract, normalize, connect, and enrich entities and concepts
• Design systems to extract insights from complex tabular data embedded in documents
• Create document intelligence capabilities for downstream search, retrieval, RAG, and agentic AI workflows
• Design evaluation frameworks using annotations, synthetic data, and production metrics
• Lead technical decisions on architectures, chunking, extraction, classification, and knowledge representation
• Partner with engineering teams to deliver scalable, production-ready AI systems
• Provide technical leadership and input into AI strategy and long-term roadmap
• Mentor applied scientists and machine learning practitioners

• PhD with demonstrable post-degree industry experience in building and deploying document understanding systems at scale
• Hands-on production experience beyond OCR, delivering measurable business impact
• Depth across document analysis, information extraction, classification, knowledge representation, evaluation, and deployment
• Proven ability to translate research into production, enabling search, retrieval, reasoning, and intelligent workflows

• collaborative mindset
• mentoring and people development
• ability to ship and measure production success
• document analysis
• information extraction
• classification