Senior Applied Scientist, Document Understanding

Thomson Reuters; Eagan (MN); On-site; USD 127,400 - 236,600; Full time

Benefits offered by this job

Flex My Way: work from anywhere up to

Grow My Way: continuous learning

Two paid volunteer days off annually

Mental Health Days

Job summary

Thomson Reuters in the United States is seeking a Senior Applied Scientist to design, build, and deploy production-grade document understanding systems powering Westlaw, PracticalLaw, and CoCounsel. You will work across semantic chunking, document enrichment, and knowledge graph construction for complex legal content.

This hands-on role requires a PhD or MS, 5+ years in production ML, and a track record of shipping models.

Qualifications

• PhD or Master’s in CS, AI, NLP or related field.

Responsibilities

• Design and deploy semantic chunking models for lengthy legal documents.

Skills

Publications

Production Python

Lead through influence

LLM-based information extraction

Knowledge graph systems

Education

PhD or Master’s in Computer Science, AI, NLP, or related field

Tools

PyTorch

Hugging Face Transformers

DeepSpeed

AzureML

AWS SageMaker

Job description

Senior Applied Scientist, Document Understanding

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

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, including work from anywhere for up to 8 weeks per year.
• Career Development and Growth: Continuous learning and skill development opportunities are available, including Grow My Way programming and a skills‑first approach.
• Industry Competitive Benefits: Flexible vacation, two company‑wide Mental Health Days off, Headspace app, retirement savings, tuition reimbursement, employee incentive programs, resources for wellbeing.
• Culture: Inclusion, belonging, flexibility, work‑life balance, and company values—Obsess over Customers, Compete to Win, Challenge Your Thinking, Act Fast/Learn Fast, Stronger Together.
• Social Impact: Two paid volunteer days off annually, pro‑bono consulting projects, ESG initiatives.
• Making a Real‑World Impact: Support customers in pursuing justice, truth, and transparency.

We comply with local laws that require upfront disclosure of the expected pay range for a position. The base compensation range for this role is $127,400 USD – $236,600 USD for eligible U.S. locations, and $100,000 CAD – $145,000 CAD for Ontario, Canada.

Equal Employment Opportunity. We are proud to be an Equal Employment Opportunity Employer providing a drug‑free workplace. We also make reasonable accommodations for qualified individuals with disabilities and sincerely held religious beliefs. For more information on requesting an accommodation, visit the Thomson Reuters website.