Senior Applied Scientist, Legal Document Understanding GenAI

Thomson Reuters; Zug; Vor Ort; CHF 150.000 - 230.000; Vollzeit

Benefits dieser Stelle

Hybrid work environment

Flex My Way

Career development

Industry competitive benefits

Global culture and inclusion

Social impact initiatives

Zusammenfassung

Thomson Reuters is seeking a senior AI researcher to design and deploy end-to-end document understanding solutions for legal, tax and accounting content. You will build semantic chunking models, document enrichment pipelines, and knowledge graphs that link entities and citations across diverse sources.

In this role, you will collaborate with product teams, publish in top venues, and drive scalable production deployments while balancing accuracy and efficiency for real-world legal research tasks.

Qualifikationen

• PhD in Computer Science, AI, NLP, or related field or Master’s with equivalent experience.
• Hands-on experience building and deploying document understanding systems or knowledge graphs using DL/LLMs.
• Ability to translate complex document understanding problems into AI applications balancing accuracy and efficiency.
• Experience leading teams in applied research settings.
• Strong programming skills (Python) and familiarity with modern DL frameworks (PyTorch, Hugging Face, DeepSpeed).
• Publications at ACL, EMNLP, ICLR, NeurIPS, SIGIR, or KDD.

Aufgaben

• Design, build, test, and deploy end-to-end AI solutions for document understanding in the legal domain.
• Develop models for semantic chunking, document enrichment, and knowledge graph construction.
• Collaborate with engineering to ensure reliable, scalable production deployment.

Kenntnisse

Hands-on experience

Leadership

Publications

Python programming

Ausbildung

PhD in Computer Science, AI, NLP, or related field

Tools

PyTorch

Hugging Face Transformers

DeepSpeed

Python

Jobbeschreibung

Thomson Reuters is seeking a senior AI researcher to design and deploy end-to-end document understanding solutions for legal, tax and accounting content. You will build semantic chunking models, document enrichment pipelines, and knowledge graphs that link entities and citations across diverse sources.

In this role, you will collaborate with product teams, publish in top venues, and drive scalable production deployments while balancing accuracy and efficiency for real-world legal research tasks.