Thomson Reuters
Senior Applied Scientist, NLP/GenAI(m/w/x)
Full-timeWith HomeofficeSenior
Zug
New Job?Nejo!
Your personal AI career agent
THThomson Reuters Enterprise Centre GmbH
Lead Applied Scientist, NLP/GenAI(m/w/x)
Zug
Full-timeWith Home OfficeSenior
AI/ML
Nejo AI Summary
Leading solution development for legal document understanding, with LLM-based knowledge graph construction and synthetic data generation. 7+ years hands-on experience building/deploying document understanding systems required. Two Mental Health Days, tuition reimbursement.
Requirements
- PhD in Computer Science, AI, NLP, or related field, or Master's with equivalent research/industry experience
- 7+ years hands-on experience building/deploying document understanding systems, information extraction pipelines, or knowledge graph construction
- Ability to translate complex document understanding problems into AI applications
- Technical leadership, mentoring, and influence
- Strong Python programming and deep learning frameworks experience
- Publications at relevant venues (ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD)
- Deep understanding of document understanding fundamentals
- Expertise in knowledge extraction and knowledge graph construction
- Expertise in LLM-based information extraction, few-shot/multi-task learning, post-training, knowledge distillation
- Solid understanding of synthetic data generation for NLP
- Solid understanding of efficiency optimization (knowledge distillation, model compression, SLM solutions)
- Solid understanding of DL/ML approaches for NLP tasks
- Experience designing annotation workflows, creating labeled datasets, evaluation frameworks
- Prior work on legal document understanding, information extraction, knowledge representation, or legal AI applications
- Prior work handling complex legal document structures
- Experience building systems for analysis, question answering, or retrieval across large document collections
- Experience with knowledge graph frameworks and methodologies for legal/enterprise applications
- Understanding of RAG and agentic workflows for enterprise knowledge
- Experience working with AzureML or AWS SageMaker
Tasks
- Lead AI solution development for legal document understanding
- Oversee advanced semantic chunking for legal documents
- Oversee document enrichment systems with taxonomies
- Oversee LLM-based knowledge graph construction pipelines
- Oversee scalable synthetic data generation systems
- Act as the technical lead
- Ensure accountability for research deliverables
- Partner with engineering for reliable software delivery at scale
- Design comprehensive evaluation strategies using expert annotation
- Apply robust training methodologies balancing performance and latency
- Lead knowledge distillation for production-ready SLMs
- Maintain scientific and technical expertise
- Inform Labs capabilities and research with novel approaches
- Determine architectures balancing accuracy, efficiency, and scalability
- Decide on semantic chunking strategies
- Decide on document classification approaches
- Decide on LLM-based knowledge extraction methods
- Decide on multi-document reasoning architectures
- Advise stakeholders on long-term AI strategy
- Develop customer and data knowledge for technical roadmaps
- Collaborate with Engineering and Product on scalable solutions
- Engage stakeholders to align capabilities with business needs
- Mentor and coach team members
- Build technical capability across the organization
Work Experience
- 7 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- AI
- NLP
- Deep Learning
- LLMs
- Python
- PyTorch
- Hugging Face Transformers
- DeepSpeed
- SLM
- DL
- ML
- RAG
- AzureML
- AWS SageMaker
Benefits
More Vacation Days
- Flexible vacation
Mental Health Support
- Two Mental Health Days
- Headspace app access
- Mental, physical, financial wellbeing resources
Retirement Plans
- Retirement savings
Additional Allowances
- Tuition reimbursement
Bonuses & Incentives
- Employee incentive programs
Purpose-Driven Work
- Two paid volunteer days
Social Impact
- Pro-bono consulting opportunities
Sustainability Focus
- ESG initiatives
Flexible Working
- Flexible work arrangements
- Flexible hybrid work model
Workation & Sabbatical
- Work from anywhere (8 weeks/year)
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Thomson Reuters Enterprise Centre GmbH and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
Not a perfect match?
- Thomson Reuters
Applied Scientist, NLP/GenAI(m/w/x)
Full-timeWith HomeofficeExperiencedZug - Thomson Reuters
Lead Applied Scientist - Legal Tech(m/w/x)
Full-timeWith HomeofficeSeniorZug - Thomson Reuters
Lead Applied Scientist I(m/w/x)
Full-timeWith HomeofficeSeniorZug - Thomson Reuters
Senior Applied Scientist, Knowledge Graphs and ML(m/w/x)
Full-timeWith HomeofficeSeniorZug
THThomson Reuters Enterprise Centre GmbH
Lead Applied Scientist, NLP/GenAI(m/w/x)
Zug
Full-timeWith Home OfficeSenior
AI/ML
Nejo AI Summary
Leading solution development for legal document understanding, with LLM-based knowledge graph construction and synthetic data generation. 7+ years hands-on experience building/deploying document understanding systems required. Two Mental Health Days, tuition reimbursement.
Requirements
- PhD in Computer Science, AI, NLP, or related field, or Master's with equivalent research/industry experience
- 7+ years hands-on experience building/deploying document understanding systems, information extraction pipelines, or knowledge graph construction
- Ability to translate complex document understanding problems into AI applications
- Technical leadership, mentoring, and influence
- Strong Python programming and deep learning frameworks experience
- Publications at relevant venues (ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD)
- Deep understanding of document understanding fundamentals
- Expertise in knowledge extraction and knowledge graph construction
- Expertise in LLM-based information extraction, few-shot/multi-task learning, post-training, knowledge distillation
- Solid understanding of synthetic data generation for NLP
- Solid understanding of efficiency optimization (knowledge distillation, model compression, SLM solutions)
- Solid understanding of DL/ML approaches for NLP tasks
- Experience designing annotation workflows, creating labeled datasets, evaluation frameworks
- Prior work on legal document understanding, information extraction, knowledge representation, or legal AI applications
- Prior work handling complex legal document structures
- Experience building systems for analysis, question answering, or retrieval across large document collections
- Experience with knowledge graph frameworks and methodologies for legal/enterprise applications
- Understanding of RAG and agentic workflows for enterprise knowledge
- Experience working with AzureML or AWS SageMaker
Tasks
- Lead AI solution development for legal document understanding
- Oversee advanced semantic chunking for legal documents
- Oversee document enrichment systems with taxonomies
- Oversee LLM-based knowledge graph construction pipelines
- Oversee scalable synthetic data generation systems
- Act as the technical lead
- Ensure accountability for research deliverables
- Partner with engineering for reliable software delivery at scale
- Design comprehensive evaluation strategies using expert annotation
- Apply robust training methodologies balancing performance and latency
- Lead knowledge distillation for production-ready SLMs
- Maintain scientific and technical expertise
- Inform Labs capabilities and research with novel approaches
- Determine architectures balancing accuracy, efficiency, and scalability
- Decide on semantic chunking strategies
- Decide on document classification approaches
- Decide on LLM-based knowledge extraction methods
- Decide on multi-document reasoning architectures
- Advise stakeholders on long-term AI strategy
- Develop customer and data knowledge for technical roadmaps
- Collaborate with Engineering and Product on scalable solutions
- Engage stakeholders to align capabilities with business needs
- Mentor and coach team members
- Build technical capability across the organization
Work Experience
- 7 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- AI
- NLP
- Deep Learning
- LLMs
- Python
- PyTorch
- Hugging Face Transformers
- DeepSpeed
- SLM
- DL
- ML
- RAG
- AzureML
- AWS SageMaker
Benefits
More Vacation Days
- Flexible vacation
Mental Health Support
- Two Mental Health Days
- Headspace app access
- Mental, physical, financial wellbeing resources
Retirement Plans
- Retirement savings
Additional Allowances
- Tuition reimbursement
Bonuses & Incentives
- Employee incentive programs
Purpose-Driven Work
- Two paid volunteer days
Social Impact
- Pro-bono consulting opportunities
Sustainability Focus
- ESG initiatives
Flexible Working
- Flexible work arrangements
- Flexible hybrid work model
Workation & Sabbatical
- Work from anywhere (8 weeks/year)
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Thomson Reuters Enterprise Centre GmbH and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Thomson Reuters Enterprise Centre GmbH
Industry
Legal
Description
The company informs the way forward by providing trusted content and technology for professionals across various sectors.
Not a perfect match?
- Thomson Reuters
Senior Applied Scientist, NLP/GenAI(m/w/x)
Full-timeWith HomeofficeSeniorZug - Thomson Reuters
Applied Scientist, NLP/GenAI(m/w/x)
Full-timeWith HomeofficeExperiencedZug - Thomson Reuters
Lead Applied Scientist - Legal Tech(m/w/x)
Full-timeWith HomeofficeSeniorZug - Thomson Reuters
Lead Applied Scientist I(m/w/x)
Full-timeWith HomeofficeSeniorZug - Thomson Reuters
Senior Applied Scientist, Knowledge Graphs and ML(m/w/x)
Full-timeWith HomeofficeSeniorZug