Lead Applied Scientist – Document Understanding

Job not on LinkedIn

🕒 May 29

🌐 United States, Canada – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote

🗽 New York, Michigan, +2 more states – Remote

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

💵 $147.6k - $274.2k / year

⏰ Full Time

🟠 Senior

🧬 Research Scientist

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 36%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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, AI, NLP, or a related field — required • 8+ years of post-degree industry experience shipping document understanding, information extraction, or knowledge graph systems into production • Production Python experience • Experience with PyTorch, Hugging Face Transformers, and DeepSpeed • Publications at ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD, or equivalent • Hands-on production experience in document layout analysis and semantic chunking beyond fixed-size or paragraph-based methods • Experience with hierarchical, multi-label document classification using domain-specific and customer-defined schemas • Experience with entity recognition and linking, relation extraction, citation parsing, and knowledge graph construction from unstructured text • Experience with LLM-based information extraction, few-shot and multi-task learning, and post-training • Experience with knowledge distillation, model compression, and SLM deployment under latency constraints • Experience with synthetic data generation and annotation workflow design • Experience designing end-to-end evaluation frameworks for document understanding • Preferred: legal document understanding, legal information extraction, or legal AI experience • Preferred: complex document structures, retrieval or QA systems, RAG and agentic workflows, knowledge graph frameworks, AzureML or AWS SageMaker

🏖️ Benefits

• Flex My Way supportive workplace policies • Flexible work arrangements, including work from anywhere for up to 8 weeks per year • Grow My Way programming and skills-first career development • Flexible vacation • Two company-wide Mental Health Days off • Access to the Headspace app • Retirement savings • Tuition reimbursement • Employee incentive programs • Resources for mental, physical, and financial wellbeing • Two paid volunteer days off annually • Pro-bono consulting project opportunities • Environmental, Social, and Governance (ESG) initiative opportunities • Health, dental, vision, disability, and life insurance programs • Competitive 401k plan with company match • Competitive vacation, sick and safe paid time off • Paid holidays, including two company mental health days off • 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 • Access to 529 Plan • Commuter benefits • Adoption & Surrogacy Assistance • Employee Stock Purchase Plan • Annual Bonus eligibility based on enterprise and individual performance