Lead Applied Scientist, NLPGenAI

Thomson Reuters

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profile Job Location:

Ann Arbor, MI - USA

profile Monthly Salary: $ 147000 - 273000
Posted on: Yesterday
Vacancies: 1 Vacancy

Job Summary

Lead Applied Scientist Document Understanding

Document understanding is a foundational intelligence layer that powers every major capability across our legal AI platformfrom search and information extraction to agentic reasoning in products like Westlaw PracticalLaw and CoCounsel. Youll 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 impactyour 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

About You

Required Qualifications

  • PhD in Computer Science AI NLP or a related field or a Masters 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

Technical Qualifications

  • 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

Preferred Qualifications

  • 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

#LI-LP2

Whats 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 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 tomorrows 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.

In the United States Thomson Reuters offers a comprehensive benefits package to our employees. Our benefit package includes market competitive health dental vision disability and life insurance programs as well as a competitive 401k plan with company addition Thomson Reuters offers market leading work life benefits with competitive vacation sick and safe paid time off paid holidays (including two company mental health days off) parental leave sabbatical leave. These benefits meet or exceeds the requirements of paid time off in accordance with any applicable state or municipal laws. Finally Thomson Reuters offers the following additional benefits: optional hospital accident and sickness insurance paid 100% by the employee; optional life and AD&D insurance paid 100% by the employee; Flexible Spending and Health Savings Accounts; fitness reimbursement; access to Employee Assistance Program; Group Legal Identity Theft Protection benefit paid 100% by employee; access to 529 Plan; commuter benefits; Adoption & Surrogacy Assistance; Tuition Reimbursement; and access to Employee Stock Purchase Plan.

Thomson Reuters complies with local laws that require upfront disclosure of the expected pay range for a position. The base compensation range varies across locations. For any eligible US locations unless otherwise noted the base compensation range for this role is $147000 - $273000. This role may also be eligible for an Annual Bonus based on a combination of enterprise and individual performance. Base pay is positioned within the range based on several factors including an individuals knowledge skills and experience with consideration given to internal equity. Base pay is one part of a comprehensive Total Reward program which also includes flexible and supportive benefits and other wellbeing programs.

This job posting will close 12/17/2025.

About Us

Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal tax accounting compliance government and media. Our products combine highly specialized software and insights to empower professionals with the data intelligence and solutions needed to make informed decisions and to help institutions in their pursuit of justice truth and transparency. Reuters part of Thomson Reuters is a world leading provider of trusted journalism and news.

As a global business we rely on the unique backgrounds perspectives and experiences of all employees to deliver on our business goals. To ensure we can do that we seek talented qualified employees in all our operations around the world regardless of race color sex/gender including pregnancy gender identity and expression national origin religion sexual orientation disability age marital status citizen status veteran status or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace.

We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law. More information on requesting an accommodation here.

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Lead Applied Scientist Document UnderstandingDocument understanding is a foundational intelligence layer that powers every major capability across our legal AI platformfrom search and information extraction to agentic reasoning in products like Westlaw PracticalLaw and CoCounsel. Youll build state-o...
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Document Intelligence from Thomson Reuters makes analyzing contracts and documents easy by leveraging the power of A.I. and the expertise of Practical Law.

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