Senior Lead: Legal Document Understanding Scientist

Thomson Reuters; Eagan (MN); On-site; USD 148,000 - 274,000; Full time

Benefits offered by this job

Tuition Reimbursement

Mental Health Days

Commuter benefits

Employee Stock Purchase Plan

Job summary

Thomson Reuters seeks an seasoned Lead Applied Scientist for Document Understanding. You will own design, development, and deployment of document understanding systems powering Westlaw, PracticalLaw, and CoCounsel.

Expect large-scale problems across legal, tax, and accounting content with measurable impact. You will lead semantic chunking, document enrichment, and knowledge graph construction, while mentoring a team of applied scientists and ML practitioners.

Qualifications

• PhD in Computer Science, AI, NLP, or related field.
• 8+ years of industry experience in document understanding, information extraction, or related areas.
• End-to-end ML lifecycle expertise: development, evaluation, optimization, distillation, deployment.
• Strong Python programming with PyTorch, Hugging Face Transformers, and DeepSpeed.
• Publishs research in leading conferences (ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD).
• Proven ability to mentor technical talent and drive measurable business impact with production AI systems.
• Experience translating advanced research into scalable products and services.
• Strong communication and collaboration across cross-functional teams.

Responsibilities

• Design and deploy semantic chunking models for long, complex legal documents across use cases.
• Build document enrichment systems using legal taxonomies.
• Develop LLM-based knowledge graph pipelines linking citations, entities, and concepts.
• Lead knowledge distillation to create latency-friendly production models.
• Design end-to-end evaluation frameworks with expert annotation and synthetic data.
• Own architectural decisions and chunking/classification/knowledge extraction approaches.
• Collaborate with engineering on delivery, reliability, and scale across product lines.
• Provide technical input to leadership on AI strategy and roadmap.
• Mentor applied scientists and ML practitioners on the team.

Skills

Python

PyTorch

Hugging Face Transformers

DeepSpeed

Mentoring teammates

Cross-functional collaboration

Research publication track record

Education

PhD in Computer Science / AI / NLP

Tools

AzureML

AWS SageMaker

Job description

Thomson Reuters seeks an seasoned Lead Applied Scientist for Document Understanding. You will own design, development, and deployment of document understanding systems powering Westlaw, PracticalLaw, and CoCounsel.

Expect large-scale problems across legal, tax, and accounting content with measurable impact. You will lead semantic chunking, document enrichment, and knowledge graph construction, while mentoring a team of applied scientists and ML practitioners.