Lead Applied Scientist, NLP/GenAI

Thomson Reuters • Frisco, TX

1d

About The Position

Lead Applied Scientist, Document Understanding Document understanding is a foundational intelligence layer that powers every major capability across our legal AI platform—from search and information extraction to agentic reasoning in products like Westlaw, PracticalLaw, and CoCounsel. You'll build state-of-the-art semantic chunking, document enrichment, and knowledge graph construction systems that serve as the cognitive foundation multiple product teams depend on, working across authoritative legal, tax, and accounting content and extraordinarily diverse customer data. This is a rare opportunity to solve publishing-quality research problems with immediate production impact—your innovations will directly shape how millions of legal professionals research, analyze, and reason over complex legal documents while advancing the capabilities that enable the next generation of intelligent legal AI agents. About the Role As a Lead Applied Scientist, you will: Innovate & Deliver at Scale Lead the design, build, test, and deployment of end-to-end AI solutions for complex document understanding tasks in the legal domain Direct the execution of large-scale projects including: advanced semantic chunking models for lengthy, non-uniformly structured legal documents with adjustable granularity; document enrichment systems with legal and customer-defined taxonomies; LLM-based knowledge graph construction pipelines that extract and link heterogeneous legal knowledge; and scalable synthetic data generation systems Serve as the technical lead and primary point of reference, ensuring full accountability for all research deliverables Partner with engineering to guarantee well-managed software delivery and reliability at scale across multiple product lines Evaluate, Optimize & Advance Capabilities Design comprehensive evaluation strategies for both component-level and end-to-end quality, leveraging expert annotation and synthetic data Apply robust training methodologies that balance performance with latency requirements Lead knowledge distillation initiatives to compress large models into production-ready SLMs Maintain scientific and technical expertise through product deliverables, published research, and intellectual property contributions Inform Labs shared capabilities and research themes through novel approaches to challenging business problems Drive Strategic Technical Direction Independently determine appropriate architectures for complex document understanding challenges, balancing accuracy, efficiency, and scalability Make critical technical decisions on semantic chunking strategies, document classification approaches, LLM-based knowledge extraction methods, and multi-document reasoning architectures Provide input to business stakeholders, mid-to-senior level leadership, and Labs leadership on long-term AI strategy Develop in-depth knowledge of TR customers and data infrastructure across multiple products to shape technical roadmaps Align, Communicate & Lead Partner closely with Engineering and Product teams to translate complex legal document understanding challenges into scalable, production-ready solutions Engage stakeholders across multiple product lines to deeply understand use case requirements, shaping objectives that align document understanding capabilities with diverse business needs including next-generation search and deep legal research Mentor and coach team members with varied ML/NLP abilities, building technical capability across the organization

Requirements

• PhD in Computer Science, AI, NLP, or a related field, or a Master's degree with equivalent research/industry experience
• 7+ years of hands-on experience building and deploying document understanding systems, information extraction pipelines, or knowledge graph construction using deep learning, LLMs, and NLP methods
• Proven ability to translate complex document understanding problems into innovative AI applications that balance accuracy and efficiency
• Demonstrated ability to provide technical leadership, mentor team members, and influence without formal authority in an applied research setting
• Strong programming skills (e.g., Python) and experience with modern deep learning frameworks (e.g., PyTorch, Hugging Face Transformers, DeepSpeed)
• Publications at relevant venues such as ACL, EMNLP, ICLR, NeurIPS, SIGIR, or KDD
• Deep understanding of document understanding fundamentals: document layout analysis, semantic chunking approaches beyond fixed-size or paragraph-based methods, document classification handling hierarchical taxonomies, imbalanced multi-label classification, and adapting to domain-specific schemas
• Expertise in knowledge extraction and knowledge graph construction: entity recognition and linking, relation extraction, citation parsing, and building graph representations from unstructured text
• Expertise in LLM-based information extraction, few-shot and multi-task learning, post-training, and knowledge distillation
• Solid understanding of synthetic data generation techniques for NLP, including query-answer generation with verification and scalable data augmentation for training specialized models
• Solid understanding of efficiency optimization including knowledge distillation, model compression, and designing SLM-based solutions that balance performance with computational constraints
• Solid understanding of DL/ML approaches used for NLP tasks
• Experience designing annotation workflows, creating high-quality labeled datasets with clear guidelines, and developing evaluation frameworks for document understanding tasks

Nice To Haves

• Prior work on legal document understanding, legal information extraction, knowledge representation including legal citations and legal domain concepts, or legal AI applications
• Prior work handling complex document structures common in legal documents: non-uniform formatting, nested hierarchies, cross-references, and embedded elements
• Experience building systems that perform analysis, question answering, or retrieval across large document collections
• Experience with knowledge graph frameworks and methodologies for legal or enterprise applications
• Understanding of RAG and agentic workflows for enterprise knowledge
• Experience working with AzureML or AWS SageMaker

Responsibilities

• Lead the design, build, test, and deployment of end-to-end AI solutions for complex document understanding tasks in the legal domain
• Direct the execution of large-scale projects including: advanced semantic chunking models for lengthy, non-uniformly structured legal documents with adjustable granularity; document enrichment systems with legal and customer-defined taxonomies; LLM-based knowledge graph construction pipelines that extract and link heterogeneous legal knowledge; and scalable synthetic data generation systems
• Serve as the technical lead and primary point of reference, ensuring full accountability for all research deliverables
• Partner with engineering to guarantee well-managed software delivery and reliability at scale across multiple product lines
• Design comprehensive evaluation strategies for both component-level and end-to-end quality, leveraging expert annotation and synthetic data
• Apply robust training methodologies that balance performance with latency requirements
• Lead knowledge distillation initiatives to compress large models into production-ready SLMs
• Maintain scientific and technical expertise through product deliverables, published research, and intellectual property contributions
• Inform Labs shared capabilities and research themes through novel approaches to challenging business problems
• Independently determine appropriate architectures for complex document understanding challenges, balancing accuracy, efficiency, and scalability
• Make critical technical decisions on semantic chunking strategies, document classification approaches, LLM-based knowledge extraction methods, and multi-document reasoning architectures
• Provide input to business stakeholders, mid-to-senior level leadership, and Labs leadership on long-term AI strategy
• Develop in-depth knowledge of TR customers and data infrastructure across multiple products to shape technical roadmaps
• Partner closely with Engineering and Product teams to translate complex legal document understanding challenges into scalable, production-ready solutions
• Engage stakeholders across multiple product lines to deeply understand use case requirements, shaping objectives that align document understanding capabilities with diverse business needs including next-generation search and deep legal research
• Mentor and coach team members with varied ML/NLP abilities, building technical capability across the organization

Benefits

• Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.
• Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.
• Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
• Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together.
• Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.
• Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree