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Thomson Reuters · 4 hours ago

Senior Applied Scientist, NLP/GenAI

Eagan, MN

Full-time

Hybrid

Senior Level

$145K/yr - $270K/yr

5+ years exp

Thomson Reuters is a leading provider of trusted content and technology for professionals across various sectors. They are seeking a Senior Applied Scientist to innovate and deliver advanced AI solutions for document understanding in the legal domain, significantly impacting how legal professionals research and analyze complex documents.

AdviceAnalyticsFinancial ServicesManagement ConsultingProfessional ServicesRisk ManagementSoftware

H1B Sponsor Likely

Responsibilities

Design, build, test, and deploy end-to-end AI solutions for complex document understanding tasks in the legal domain

Develop advanced models for semantic chunking of lengthy, non-uniformly structured legal documents with adjustable granularity levels for different use cases

Build document enrichment systems that classify documents according to legal and customer-defined taxonomies and extract rich metadata

Create LLM-based knowledge graph construction pipelines that extract and link heterogeneous legal knowledge including citations, entities, and legal concepts across diverse legal content

Develop scalable synthetic data generation systems to support model training, simulate complex legal research queries and generate hallucination-free answers

Work in collaboration with engineering to ensure well-managed software delivery and reliability at scale

Develop comprehensive data and evaluation strategies for both component-level and end-to-end quality, leveraging expert human annotation and synthetic data generation

Apply robust training and evaluation methodologies that balance model performance with latency requirements, particularly for SLM-based solutions

Apply knowledge distillation techniques to compress large models into efficient SLMs suitable for production deployment

Independently determine appropriate architectures for challenging document understanding problems including: semantic chunking strategies that handle diverse document formats, preserve legal document structure, and adapt to different granularity needs; document classification approaches that work across varying legal taxonomies and generalize to customer-defined schemas; LLM-based knowledge extraction methods that handle challenges like citation recognition errors and contextual references; multi-document reasoning architectures for generating synthetic multi-hop queries that reflect complex legal research patterns

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

Maintain scientific and technical expertise in one or more relevant areas as demonstrated through product deliverables, published research at top venues (e.g., ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD), and intellectual property

Qualification

NLPDeep LearningKnowledge GraphsDocument UnderstandingPythonPyTorchHugging Face TransformersSynthetic Data GenerationModel CompressionLegal Domain ExperiencePublicationsSoft Skills

Required

PhD in Computer Science, AI, NLP, or a related field, or a Master's with equivalent research/industry experience

5+ 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

Professional experience scaling yourself and leading through others, 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, 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

Preferred

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 with 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

Publications at relevant venues such as ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD

Experience working with AzureML or AWS SageMaker

Benefits

Hybrid Work Model: We’ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) for our office-based roles while delivering a seamless experience that is digitally and physically connected.

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.

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 match.

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.

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.

Company

Thomson Reuters

Glassdoor3.0

Thomson Reuters delivers critical information from the financial, legal, accounting, intellectual property, science, and media markets.

Founded in 2008

Toronto, Ontario, CAN

10001+ employees

http://thomsonreuters.com

H1B Sponsorship

Thomson Reuters has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)

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2025 (1)

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