Lead AI Scientist, Legal Search & Knowledge Graph

Thomson Reuters Corp.

Zug

Hybrid

CHF 150.000 - 190.000

Vollzeit

vor 34 Stunden
Sei unter den ersten Bewerbenden
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Benefits dieser Stelle

Hybrid Work Model
Grow My Way
Mental Health Days
Tuition Reimbursement
Retirement Savings

Zusammenfassung

Thomson Reuters Corp. seeks a Lead Applied Scientist to architect and deploy AI solutions for complex document understanding in legal, tax, and professional services.

You will lead end-to-end projects, design semantic chunking, enrichment, and knowledge graphs, and drive production-ready research across multiple teams. The role offers hybrid work between Zug or London, collaboration with Engineering and Product, mentorship for the ML/NLP team, and opportunities to publish and shape strategic AI

Qualifikationen

  • PhD in CS/AI/NLP or MSc with equivalent research/industry experience.
  • Hands-on experience building document understanding systems and knowledge graphs.
  • Proven ability to lead research-based AI projects and deliver production-ready solutions.

Aufgaben

  • Lead design, build, test, and deployment of end-to-end AI solutions for document understanding in legal domains.
  • Direct large-scale projects on semantic chunking, enrichment, and knowledge graph pipelines.
  • Mentor team members and partner with engineering for scalable, reliable delivery.

Kenntnisse

Document understanding
Knowledge graph construction
LLMs
NLP
Python
PyTorch
Hugging Face Transformers
DeepSpeed

Ausbildung

PhD in Computer Science or related field

Tools

PyTorch
Hugging Face Transformers
DeepSpeed

Jobbeschreibung

Thomson Reuters Corp. seeks a Lead Applied Scientist to architect and deploy AI solutions for complex document understanding in legal, tax, and professional services.

You will lead end-to-end projects, design semantic chunking, enrichment, and knowledge graphs, and drive production-ready research across multiple teams. The role offers hybrid work between Zug or London, collaboration with Engineering and Product, mentorship for the ML/NLP team, and opportunities to publish and shape strategic AI

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