Lead NLP Scientist: Document Understanding at Scale

Thomson Reuters; Ann Arbor (MI); On-site; USD 147,600 - 274,200; Full time

Benefits offered by this job

Flexible benefits

Professional growth

Mental health days off

Retirement plan

Volunteer days

Job summary

Thomson Reuters seeks a Lead Applied Scientist for Document Understanding to own the full stack from design to production deployment. You will advance semantic chunking, document enrichment, and knowledge graph construction at scale for legal and accounting content.

Requires a PhD and 8+ years shipping NLP/IE/knowledge graph systems, with strong PyTorch and Transformers experience. You will mentor team members, partner with engineers, and influence AI strategy and roadmap.

Qualifications

• PhD in Computer Science, AI, NLP, or a related field; required.
• 8+ years of post-degree industry experience shipping document understanding or knowledge graph systems into production.
• Publications at ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD, or equivalent.
• Production Python and experience with PyTorch, Hugging Face Transformers, and DeepSpeed.

Responsibilities

• Design and deploy semantic chunking models for lengthy legal documents with adjustable granularity across use cases.
• Build document enrichment systems using legal and customer-defined taxonomies.
• Develop LLM-based knowledge graph construction pipelines that extract and link citations, entities, and legal concepts.
• Lead knowledge distillation to compress large models into latency-constrained, production-ready systems.
• Design evaluation frameworks using expert annotation and synthetic data.
• Own technical decisions on architecture, chunking strategy, classification approach, and knowledge extraction methods.

Skills

Publications in NLP

Mentoring

Education

PhD in Computer Science, AI or NLP

Tools

PyTorch

HuggingFace Transformers

DeepSpeed

Job description

Thomson Reuters seeks a Lead Applied Scientist for Document Understanding to own the full stack from design to production deployment. You will advance semantic chunking, document enrichment, and knowledge graph construction at scale for legal and accounting content.

Requires a PhD and 8+ years shipping NLP/IE/knowledge graph systems, with strong PyTorch and Transformers experience. You will mentor team members, partner with engineers, and influence AI strategy and roadmap.