Senior Applied Scientist, Document Understanding
Thomson ReutersAbout the role
Senior Applied Scientist, Document Understanding
About the Role
This is an applied science position focused on designing, building, and deploying production-grade document understanding systems that power Westlaw, PracticalLaw, and CoCounsel.
You will work across semantic chunking, document enrichment, and knowledge graph construction for complex legal, tax, and accounting content — delivering foundational intelligence that multiple product teams depend on at scale.
About You
You hold a PhD or Master's in Computer Science, AI, NLP, or a related field, with 5+ years of post-degree industry experience shipping document understanding, information extraction, or knowledge graph systems into production. You have hands-on depth across model development, distillation, evaluation, and deployment. You work independently, lead through influence in an applied research setting, and measure success by what ships and performs in production.
What You'll Do
Design and deploy semantic chunking models for lengthy, non-uniformly structured legal documents with adjustable granularity across use cases
Build document enrichment systems that classify documents according to legal and customer-defined taxonomies and extract rich metadata
Develop LLM-based knowledge graph construction pipelines that extract and link citations, entities, and legal concepts across diverse legal content
Build scalable synthetic data generation systems for model training, multi-hop query simulation, and hallucination-free answer generation
Apply knowledge distillation techniques to compress large models into latency-constrained, production-ready SLMs
Design evaluation frameworks — component-level and end-to-end — using expert annotation and synthetic data
Drive independent technical decisions on chunking strategy, classification approach, knowledge extraction methods, and multi-document reasoning architecture
Partner with engineering on delivery, reliability, and scale across multiple product lines
Contribute to published research at venues such as ACL, EMNLP, ICLR, NeurIPS, SIGIR, and KDD, and to intellectual property
Required Qualifications
PhD or Master's in Computer Science, AI, NLP, or a related field
5+ years of post-degree industry experience shipping document understanding, information extraction, or knowledge graph systems into production — not research-only experience
Publications at ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD, or equivalent
Experience leading through influence in an applied research setting
Production Python and experience with PyTorch, Hugging Face Transformers, and DeepSpeed
Hands-on production depth required in:
Document layout analysis and semantic chunking beyond fixed-size or paragraph-based methods
Hierarchical, multi-label document classification with domain-specific and customer-defined schemas
Entity recognition and linking, relation extraction, citation parsing, and knowledge graph construction from unstructured text
LLM-based information extraction, few-shot and multi-task learning, and post-training
Knowledge distillation, model compression, and SLM deployment under latency constraints
Synthetic data generation for NLP: query-answer generation with verification and scalable data augmentation
Annotation workflow design and evaluation framework development for document understanding tasks
Preferred Qualifications
Legal document understanding, legal information extraction, or legal AI applications
Complex document structures common in legal content: nested hierarchies, cross-references, non-uniform formatting, and embedded elements
Retrieval, QA, or analysis systems over large document collections
Knowledge graph frameworks for legal or enterprise applications
RAG and agentic workflows for enterprise knowledge systems
AzureML or AWS SageMaker
#LI-LP2
What’s in it For You?
Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangeme
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