Senior AI Scientist, Document Understanding & Knowledge Graphs

Reuters; New York (NY); On-site; USD 148,000 - 274,000; Full time

Benefits offered by this job

Flexible vacation

Mental Health Days

Tuition reimbursement

Student loan assistance

Job summary

Thomson Reuters seeks a Lead Applied Scientist to own the design, development, and deployment of document understanding systems powering Westlaw, PracticalLaw, and CoCounsel.

The role covers semantic chunking, document enrichment, knowledge graphs, and synthetic data generation across legal content. You will mentor teams, drive AI strategy, and collaborate across product lines to deliver scalable, reliable systems.

Qualifications

• PhD in Computer Science, AI, NLP or related field.
• 8+ years of industry experience building and scaling document understanding, information extraction, knowledge graph, or applied NLP solutions.
• Strong Python programming with hands-on PyTorch experience, production deployment.
• Track record of publishing at major conferences (ACL/EMNLP/ICLR/NIPS/SIGIR/KDD).

Responsibilities

• Design and deploy semantic chunking models for long, non-uniform legal docs with adjustable granularity.
• Build document enrichment systems using legal and customer-defined taxonomies.
• Develop LLM-based knowledge graph construction pipelines to extract and link citations, entities, and concepts.
• Lead knowledge distillation to produce latency-friendly production models.
• Design evaluation frameworks for end-to-end document understanding and ML components.

Skills

Python programming

ML lifecycle

Mentoring

Cross-functional

Education

PhD in CS/AI/NLP

Tools

PyTorch

Hugging Face Transformers

DeepSpeed

Job description

Thomson Reuters seeks a Lead Applied Scientist to own the design, development, and deployment of document understanding systems powering Westlaw, PracticalLaw, and CoCounsel.

The role covers semantic chunking, document enrichment, knowledge graphs, and synthetic data generation across legal content. You will mentor teams, drive AI strategy, and collaborate across product lines to deliver scalable, reliable systems.