Lead Applied Scientist, Document Understanding

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🔥 0 minutes ago

🌐 United States, Canada – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote

🗽 New York, Minnesota, +1 more states – Remote

🗽 New York – Remote ❄️ Minnesota – Remote 🤠 Texas – Remote

💵 $147.6k - $274.2k / year

⏰ Full Time

🟠 Senior

🧬 Research Scientist

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Thomson Reuters

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 2008

💼 Consulting

⚖️ Legal

🛡️ Insurance

Consulting • Legal • Insurance

Thomson Reuters is a global content and technology company that provides professionals with reliable and accurate solutions across the legal, tax and accounting, international trade, and risk management sectors. The company offers a range of products including legal research tools, tax preparation software, compliance and regulatory solutions, and media services like Reuters for global news. With significant investments in generative AI, Thomson Reuters continues to innovate in helping professionals optimize their workflows and enhance their decision-making. Their platforms serve various industries such as law firms, corporations, tax professionals, and media organizations, providing essential tools that combine powerful technology with in-depth expert content.

📋 Description

• Own the design, development, and production deployment of document understanding systems powering Westlaw, PracticalLaw, and CoCounsel • Design and deploy semantic chunking models for lengthy, non-uniformly structured legal documents • Build document enrichment systems using legal and customer-defined taxonomies • Develop LLM-based knowledge graph construction pipelines extracting and linking citations, entities, and legal concepts • Lead knowledge distillation efforts to compress large models into latency-constrained, production-ready SLMs • Design component-level and end-to-end evaluation frameworks using expert annotation and synthetic data • Own technical decisions on architecture, chunking strategy, classification approach, and knowledge extraction methods • Partner with engineering on delivery, reliability, and scale across multiple product lines • Provide technical input to senior leadership on AI strategy and roadmap • Mentor applied scientists and ML practitioners

🎯 Requirements

• PhD in Computer Science, Artificial Intelligence, Natural Language Processing, or a related field • 8+ years of industry experience building and scaling document understanding, information extraction, knowledge graph, or applied NLP solutions • Expertise across the end-to-end ML lifecycle, including model development, evaluation, optimization, distillation, and production deployment • Strong Python programming skills • Hands-on experience with PyTorch, Hugging Face Transformers, and DeepSpeed • Track record of publishing research in leading conferences such as ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD, or equivalent • Ability to mentor technical talent and drive measurable business impact through production-ready AI systems • Experience translating advanced research into scalable, high-performing products and services • Strong communication and cross-functional collaboration skills • Hands-on production depth in document layout analysis and semantic chunking beyond fixed-size or paragraph-based methods • Hands-on production depth in hierarchical, multi-label document classification with domain-specific and customer-defined schemas • Hands-on production depth in entity recognition and linking, relation extraction, citation parsing, and knowledge graph construction from unstructured text • Hands-on production depth in LLM-based information extraction, few-shot and multi-task learning, and post-training • Hands-on production depth in knowledge distillation, model compression, and SLM deployment under latency constraints • Hands-on production depth in synthetic data generation and annotation workflow design • Hands-on production depth in end-to-end evaluation framework design for document understanding • Preferred: Legal document understanding, legal IE, or legal AI experience • Preferred: Complex document structures, retrieval or QA systems, RAG and agentic workflows, knowledge graph frameworks, AzureML or AWS SageMaker

🏖️ Benefits

• Flexible work arrangements, including work from anywhere for up to 8 weeks per year • Flexible vacation • Two company-wide Mental Health Days off • Headspace app access • Retirement savings • Tuition reimbursement • Employee incentive programs • Mental, physical, and financial wellbeing resources • Two paid volunteer days off annually • Health, dental, vision, disability, and life insurance programs • Competitive 401(k) plan with company match • Sick and safe paid time off • Paid holidays • Parental leave • Sabbatical leave • Optional hospital, accident and sickness insurance • Optional life and AD&D insurance • Flexible Spending and Health Savings Accounts • Fitness reimbursement • Employee Assistance Program • Group Legal Identity Theft Protection benefit • 529 Plan access • Commuter benefits • Adoption & Surrogacy Assistance • Employee Stock Purchase Plan • Annual Bonus based on enterprise and individual performance (role may be eligible)