Lead Applied Scientist, Search - NLP/GenAI in Niedergebra

Lead Applied Scientist, Search - NLP/GenAIThis position is based in either Zug, Switzerland or London, UK.Want to use your experience of building search-led AI solutions to enhance our leading products in the tax, legal and professional services industries? 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 RoleLead the design, build, test, and deployment of end-to-end AI solutions for complex document understanding tasks in the legal domainDirect 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 systemsServe as the technical lead and primary point of reference, ensuring full accountability for all research deliverablesPartner with engineering to guarantee well-managed software delivery and reliability at scale across multiple product linesEvaluate, Optimize & Advance CapabilitiesDesign comprehensive evaluation strategies for both component-level and end-to-end quality, leveraging expert annotation and synthetic dataApply robust training methodologies that balance performance with latency requirementsLead knowledge distillation initiatives to compress large models into production-ready SLMsMaintain scientific and technical expertise through product deliverables, published research, and intellectual property contributionsInform Labs shared capabilities and research themes through novel approaches to challenging business problemsDrive Strategic Technical DirectionIndependently determine appropriate architectures for complex document understanding challenges, balancing accuracy, efficiency, and scalabilityMake critical technical decisions on semantic chunking strategies, document classification approaches, LLM-based knowledge extraction methods, and multi-document reasoning architecturesProvide input to business stakeholders, mid-to-senior level leadership, and Labs leadership on long-term AI strategyDevelop in-depth knowledge of TR customers and data infrastructure across multiple products to shape technical roadmapsAlign, Communicate & Lead Partner closely with Engineering and Product teams to translate complex legal document understanding challenges into scalable, production-ready solutionsEngage 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 researchMentor and coach team members with varied ML #J-18808-Ljbffr