Senior Applied Scientist, Search - NLP/GenAI

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

SKILLS

Semantic Chunking Document Classification Knowledge Graph Construction LLM-based Information Extraction Synthetic Data Generation Python PyTorch Knowledge Distillation

FULL DESCRIPTION

Senior Applied Scientist, Search - NLP/GenAI

[Employer hidden — sign up to reveal] is hiring a Senior Applied Scientist to develop search and NLP/GenAI solutions for document understanding. This is a hybrid role based in Zug, Switzerland or London, UK.

About the Role

As a Senior Applied Scientist you will:

  • Innovate & Deliver: Design, build, test, and deploy end-to-end AI solutions for complex document understanding tasks in the legal domain.
  • Evaluate & Optimize: Develop comprehensive data and evaluation strategies for both component-level and end-to-end quality.
  • Drive Technical Decisions: Independently determine appropriate architectures for challenging document understanding problems.
  • Align & Communicate: Partner closely with Engineering and Product teams to translate complex legal document understanding challenges into scalable solutions.
  • Advance the Field: Maintain scientific and technical expertise in relevant areas.

About You

  • PhD in Computer Science, AI, NLP, or related field, or Master's with equivalent experience.
  • Hands-on experience building and deploying document understanding systems, information extraction pipelines, or knowledge graph construction using deep learning, LLMs, and NLP.
  • Proven ability to translate complex document understanding problems into innovative AI applications.
  • Professional experience scaling yourself and leading through others in an applied research setting.
  • Strong programming skills (e.g., Python) and experience with deep learning frameworks (e.g., PyTorch, Hugging Face Transformers, DeepSpeed).
  • Publications at relevant venues such as ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD.

Technical Qualifications

  • Deep understanding of document understanding fundamentals: layout analysis, semantic chunking, document classification.
  • Expertise in knowledge extraction and graph construction: entity recognition, relation extraction, citation parsing.
  • Expertise in LLM-based information extraction, few-shot learning, post-training, and knowledge distillation.
  • Solid understanding of synthetic data generation techniques for NLP.
  • Solid understanding of efficiency optimization including model compression and SLM-based solutions.
  • Experience designing annotation workflows and evaluation frameworks.

What’s in it For You?

  • Hybrid Work Model: 2-3 days a week in the office.
  • Flexibility & Work-Life Balance: Flex My Way policies, work from anywhere up to 8 weeks per year.
  • Career Development and Growth: Continuous learning and skills-first approach.
  • Industry Competitive Benefits: Flexible vacation, mental health days, retirement savings, tuition reimbursement.
  • Culture: Globally recognized for inclusion and belonging.
  • Social Impact: Two paid volunteer days off, pro-bono consulting.

[Employer hidden — sign up to reveal] is an Equal Employment Opportunity Employer. More information at thomsonreuters.com.

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