Lead Applied Scientist, Search - NLP/GenAI

🔒 Confidential Employer
Posted 7 May 2026
LOCATION
Zug, Switzerland; London, UK
TYPE
Full-time
LEVEL
Mid-Senior level
CATEGORY
Data & Analytics
This employer holds a UK Home Office sponsor license — sponsorship for this specific role is at the employer’s discretion

SKILLS

Natural Language Processing Generative AI Deep Learning Python PyTorch Knowledge Graph Construction Semantic Chunking Document Understanding

FULL DESCRIPTION

Lead Applied Scientist, Search - NLP/GenAI

[Employer hidden — sign up to reveal] is seeking a Lead Applied Scientist to build state-of-the-art document understanding systems for their legal AI platform. This hybrid role is based in Zug, Switzerland or London, UK and offers a full-time position.

About the Role

As a Lead Applied Scientist, you will:

  • Lead the design, build, test, and deployment of end-to-end AI solutions for complex document understanding tasks in the legal domain
  • Direct execution of large-scale projects including advanced semantic chunking, document enrichment, LLM-based knowledge graph construction, and scalable synthetic data generation
  • Serve as technical lead and primary point of reference for deliverables
  • Partner with engineering to ensure reliable software delivery at scale
  • Design comprehensive evaluation strategies and apply robust training methodologies
  • Lead knowledge distillation initiatives and maintain scientific expertise through publications and IP
  • Independently determine appropriate architectures for document understanding challenges
  • Mentor and coach team members across varied ML/NLP abilities

About You

You are a fit if you have:

  • PhD in Computer Science, AI, NLP, or related field (or Master's with equivalent experience)
  • Hands-on experience deploying document understanding systems, information extraction, or knowledge graph construction using deep learning, LLMs, and NLP
  • Proven ability to translate complex problems into AI applications
  • Technical leadership and mentoring experience
  • Strong programming in Python and experience with PyTorch, Hugging Face Transformers, DeepSpeed
  • Publications at ACL, EMNLP, ICLR, NeurIPS, SIGIR, or KDD

Technical Qualifications

  • Deep understanding of document understanding fundamentals (layout analysis, semantic chunking, classification)
  • Expertise in knowledge extraction and knowledge graph construction (entity linking, relation extraction, citation parsing)
  • Expertise in LLM-based information extraction, few-shot learning, post-training, knowledge distillation
  • Solid understanding of synthetic data generation and efficiency optimization
  • Experience designing annotation workflows and evaluation frameworks

What’s in it For You?

  • Hybrid Work Model (2-3 days in office)
  • Flexibility & Work-Life Balance with 'Flex My Way' policies, including work from anywhere up to 8 weeks per year
  • Career Development and Growth with skills-first approach
  • Industry Competitive Benefits including flexible vacation, mental health days, retirement savings, tuition reimbursement
  • Culture of inclusion, belonging, and work-life balance
  • Social Impact with paid volunteer days and ESG initiatives

About [Employer hidden — sign up to reveal]

[Employer hidden — sign up to reveal] informs the way forward by bringing together trusted content and technology for professionals in legal, tax, accounting, compliance, government, and media. We are an equal opportunity employer and provide reasonable accommodations. Learn more at thomsonreuters.com.

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