Thomson Reuters Enterprise Centre GmbH
Lead Applied Scientist, NLP/GenAI(m/w/x)
Vollzeitmit HomeofficeSenior
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THThomson Reuters
Senior Applied Scientist, NLP/GenAI(m/w/x)
Zug
Vollzeitmit HomeofficeSenior
AI/ML
Data Science
Nejo KI-Zusammenfassung
At a legal tech provider, building LLM-based KG pipelines for legal document understanding and enrichment. 5+ years building document understanding systems or KG pipelines required. Work from anywhere up to 8 weeks/year.
Anforderungen
- PhD in CS, AI, NLP, or related field, or Master's with equivalent experience
- 5+ years experience building/deploying document understanding systems, IE pipelines, or KG construction
- Ability to translate complex document understanding problems into AI applications
- Professional experience scaling and leading in applied research
- Strong programming skills (Python) and modern 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
- Experience designing annotation workflows, creating labeled datasets, and evaluation frameworks
- Prior work on legal document understanding, IE, knowledge representation, or legal AI
- Prior work handling complex legal document structures
- Experience building systems for analysis, Q&A, or retrieval across large document collections
- Experience with knowledge graph frameworks for legal/enterprise applications
- Understanding of RAG and agentic workflows
- Publications at relevant venues (ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD)
- Experience with AzureML or AWS SageMaker
Aufgaben
- Design, build, test, and deploy AI solutions for legal document understanding.
- Develop advanced models for semantic chunking of legal documents.
- Build document enrichment systems for classification and metadata extraction.
- Create LLM-based knowledge graph construction pipelines.
- Develop scalable synthetic data generation systems.
- Simulate complex legal research queries.
- Generate hallucination-free answers.
- Collaborate with engineering for software delivery.
- Ensure software reliability at scale.
- Develop comprehensive data and evaluation strategies.
- Leverage human annotation and synthetic data for evaluation.
- Apply robust training and evaluation methodologies.
- Balance model performance with latency requirements.
- Apply knowledge distillation techniques.
- Compress large models into efficient SLMs.
- Optimize and deploy efficient SLM solutions.
- Determine architectures for semantic chunking.
- Address diverse document formats and structures.
- Adapt chunking granularity.
- Determine architectures for document classification.
- Support varying legal taxonomies and customer schemas.
- Determine architectures for LLM-based knowledge extraction.
- Handle citation errors and contextual references.
- Determine architectures for multi-document reasoning.
- Generate synthetic multi-hop queries.
- Balance accuracy, efficiency, and scalability.
- Solve real-world document challenges.
- Handle diverse document formats and content types.
- Partner with Engineering and Product teams.
- Translate legal document challenges into solutions.
- Engage stakeholders across product lines.
- Understand use case requirements.
- Shape objectives for document understanding.
- Align capabilities with diverse business needs.
- Support next-generation search and legal research.
- Maintain scientific and technical expertise.
- Demonstrate expertise through product deliverables.
- Publish research at top venues.
- Contribute to intellectual property.
Berufserfahrung
- 5 Jahre
Ausbildung
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- PyTorch
- Hugging Face Transformers
- DeepSpeed
- LLMs
- SLM
- RAG
- AzureML
- AWS SageMaker
Benefits
Flexibles Arbeiten
- Hybrid work model
- Flex My Way policies
- Flexible work arrangements
Workation & Sabbatical
- Work from anywhere (up to 8 weeks/year)
Weiterbildungsangebote
- Continuous learning culture
- Skill development
- Grow My Way programming
Sonstige Vorteile
- Skills-first approach
Mehr Urlaubstage
- Flexible vacation
Mentale Gesundheitsförderung
- Two company-wide Mental Health Days off
- Headspace app access
- Mental wellbeing resources
Betriebliche Altersvorsorge
- Retirement savings
Sonstige Zulagen
- Tuition reimbursement
- Financial wellbeing resources
Boni & Prämien
- Employee incentive programs
Gesundheits- & Fitnessangebote
- Physical wellbeing resources
Gemeinnützige Ausrichtung
- Social Impact Institute
- Two paid volunteer days off annually
- Pro-bono consulting project opportunities
Fokus auf Nachhaltigkeit
- ESG initiative involvement
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens Thomson Reuters erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
Noch nicht perfekt?
- Thomson Reuters
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Lead Applied Scientist - Legal Tech(m/w/x)
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Senior Applied Scientist, Knowledge Graphs and ML(m/w/x)
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Lead Applied Scientist I(m/w/x)
Vollzeitmit HomeofficeSeniorZug
THThomson Reuters
Senior Applied Scientist, NLP/GenAI(m/w/x)
Zug
Vollzeitmit HomeofficeSenior
AI/ML
Data Science
Nejo KI-Zusammenfassung
At a legal tech provider, building LLM-based KG pipelines for legal document understanding and enrichment. 5+ years building document understanding systems or KG pipelines required. Work from anywhere up to 8 weeks/year.
Anforderungen
- PhD in CS, AI, NLP, or related field, or Master's with equivalent experience
- 5+ years experience building/deploying document understanding systems, IE pipelines, or KG construction
- Ability to translate complex document understanding problems into AI applications
- Professional experience scaling and leading in applied research
- Strong programming skills (Python) and modern 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
- Experience designing annotation workflows, creating labeled datasets, and evaluation frameworks
- Prior work on legal document understanding, IE, knowledge representation, or legal AI
- Prior work handling complex legal document structures
- Experience building systems for analysis, Q&A, or retrieval across large document collections
- Experience with knowledge graph frameworks for legal/enterprise applications
- Understanding of RAG and agentic workflows
- Publications at relevant venues (ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD)
- Experience with AzureML or AWS SageMaker
Aufgaben
- Design, build, test, and deploy AI solutions for legal document understanding.
- Develop advanced models for semantic chunking of legal documents.
- Build document enrichment systems for classification and metadata extraction.
- Create LLM-based knowledge graph construction pipelines.
- Develop scalable synthetic data generation systems.
- Simulate complex legal research queries.
- Generate hallucination-free answers.
- Collaborate with engineering for software delivery.
- Ensure software reliability at scale.
- Develop comprehensive data and evaluation strategies.
- Leverage human annotation and synthetic data for evaluation.
- Apply robust training and evaluation methodologies.
- Balance model performance with latency requirements.
- Apply knowledge distillation techniques.
- Compress large models into efficient SLMs.
- Optimize and deploy efficient SLM solutions.
- Determine architectures for semantic chunking.
- Address diverse document formats and structures.
- Adapt chunking granularity.
- Determine architectures for document classification.
- Support varying legal taxonomies and customer schemas.
- Determine architectures for LLM-based knowledge extraction.
- Handle citation errors and contextual references.
- Determine architectures for multi-document reasoning.
- Generate synthetic multi-hop queries.
- Balance accuracy, efficiency, and scalability.
- Solve real-world document challenges.
- Handle diverse document formats and content types.
- Partner with Engineering and Product teams.
- Translate legal document challenges into solutions.
- Engage stakeholders across product lines.
- Understand use case requirements.
- Shape objectives for document understanding.
- Align capabilities with diverse business needs.
- Support next-generation search and legal research.
- Maintain scientific and technical expertise.
- Demonstrate expertise through product deliverables.
- Publish research at top venues.
- Contribute to intellectual property.
Berufserfahrung
- 5 Jahre
Ausbildung
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- PyTorch
- Hugging Face Transformers
- DeepSpeed
- LLMs
- SLM
- RAG
- AzureML
- AWS SageMaker
Benefits
Flexibles Arbeiten
- Hybrid work model
- Flex My Way policies
- Flexible work arrangements
Workation & Sabbatical
- Work from anywhere (up to 8 weeks/year)
Weiterbildungsangebote
- Continuous learning culture
- Skill development
- Grow My Way programming
Sonstige Vorteile
- Skills-first approach
Mehr Urlaubstage
- Flexible vacation
Mentale Gesundheitsförderung
- Two company-wide Mental Health Days off
- Headspace app access
- Mental wellbeing resources
Betriebliche Altersvorsorge
- Retirement savings
Sonstige Zulagen
- Tuition reimbursement
- Financial wellbeing resources
Boni & Prämien
- Employee incentive programs
Gesundheits- & Fitnessangebote
- Physical wellbeing resources
Gemeinnützige Ausrichtung
- Social Impact Institute
- Two paid volunteer days off annually
- Pro-bono consulting project opportunities
Fokus auf Nachhaltigkeit
- ESG initiative involvement
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens Thomson Reuters erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
Über das Unternehmen
Thomson Reuters
Branche
Legal
Beschreibung
The company provides trusted content and technology for professionals in legal, tax, accounting, compliance, government, and media.
Noch nicht perfekt?
- Thomson Reuters Enterprise Centre GmbH
Lead Applied Scientist, NLP/GenAI(m/w/x)
Vollzeitmit HomeofficeSeniorZug - Thomson Reuters
Applied Scientist, NLP/GenAI(m/w/x)
Vollzeitmit HomeofficeBerufserfahrenZug - Thomson Reuters
Lead Applied Scientist - Legal Tech(m/w/x)
Vollzeitmit HomeofficeSeniorZug - Thomson Reuters
Senior Applied Scientist, Knowledge Graphs and ML(m/w/x)
Vollzeitmit HomeofficeSeniorZug - Thomson Reuters
Lead Applied Scientist I(m/w/x)
Vollzeitmit HomeofficeSeniorZug