Lead Applied Scientist, NLP/GenAI

Join to apply for the Lead Applied Scientist, NLP/GenAI role at Thomson Reuters Overview Thomson Reuters is building the foundational document understanding systems that power AI across Westlaw, Practical Law, and CoCounsel. This work spans semantic chunking, document enrichment, and knowledge graph construction—all essential to next‑generation search, reasoning, and intelligent legal agents used by millions of professionals. What You’ll Lead End‑to‑end AI solutions for semantic chunking, document enrichment, knowledge extraction, and knowledge graph construction Large‑scale projects involving long‑document modeling, legal taxonomies, multi‑document reasoning, and synthetic data generation Technical strategy, architecture choices, and research direction across document understanding capabilities Collaboration with engineering to deliver reliable, scalable systems across multiple product lines Knowledge distillation, model compression, and optimization of SLMs for production Evaluation frameworks, annotation strategies, and quality measurement for document understanding What You Bring PhD or Master’s with equivalent experience in NLP, ML, AI, or related fields 7+ years building document understanding, information extraction, or KG systems Proven technical leadership; ability to mentor and influence in applied research environments Strong deep learning expertise (PyTorch, Hugging Face, DeepSpeed) Track record of impactful publications (ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD) Ability to design scalable architectures balancing accuracy, efficiency, and latency Technical Skills Semantic chunking, layout analysis, hierarchical document classification Entity and relation extraction, citation parsing, knowledge graph construction LLM‑based extraction, few‑shot/multi‑task learning, post‑training, distillation Synthetic data generation for NLP and dataset design Annotation workflow design and evaluation methodologies Optimization techniques for SLMs and production‑ready model delivery Nice to Have Experience with legal documents, legal search, or enterprise knowledge systems Work on long‑document QA, multi‑document reasoning, or RAG/agentic workflows Hands‑on experience with KG frameworks or large‑corpus analytics Familiarity with AzureML or AWS SageMaker Benefits Flexibility & Work‑Life Balance: Flex My Way policies and work‑from‑anywhere for up to 8 weeks per year Career Development and Growth: Grow My Way programming and skills‑first approach Industry Competitive Benefits: Flexible vacation, mental health days, Headspace, retirement savings, tuition reimbursement, employee incentive programs, and wellness resources Culture: Inclusion, belonging, flexibility, and core values of customer obsession and teamwork Social Impact: Paid volunteer days, pro‑bono consulting, and ESG initiatives Making a Real‑World Impact: Supporting justice, truth, and transparency for customers worldwide Compensation For any eligible US locations, the base compensation range is $147,000 – $273,000. This role may also be eligible for an annual bonus based on enterprise and individual performance. This job posting will close 12/17/2025. About Us Thomson Reuters informs the way forward by bringing together trusted content and technology to empower professionals across legal, tax, accounting, compliance, government, and media. Our products combine specialized software and insights to help institutions pursue justice, truth, and transparency. Equal Employment Opportunity Thomson Reuters is a proud Equal Employment Opportunity Employer. We provide a drug‑free workplace, make reasonable accommodations for qualified individuals with disabilities and sincerely held religious beliefs, and comply with all applicable laws. Referrals increase your chances of interviewing at Thomson Reuters by 2x. #J-18808-Ljbffr