Lead AI Scientist, Document Understanding & Knowledge Graphs

Thomson Reuters Foundation; New York (NY); Presencial; USD 148 000 - 274 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Flexible vacation

Mental Health Days

Headspace app

Retirement savings

Tuition reimbursement

Wellbeing programs

Resumo da oferta

Thomson Reuters Foundation in New York seeks a Lead Applied Scientist to own design, development, and production deployment of document understanding systems powering Westlaw, PracticalLaw, and CoCounsel. You will advance semantic chunking, enrichment via legal taxonomies, and LLM-based knowledge graphs.

You will lead distillation to latency-aware models, define evaluation frameworks, and mentor a team of applied scientists while shaping AI strategy for multiple product lines.

Qualificações

• PhD in Computer Science, AI, NLP, or related field.
• 8+ years in document understanding, information extraction, knowledge graphs, or NLP.
• End-to-end ML lifecycle experience including deployment.
• Strong Python with PyTorch/Transformers/DeepSpeed experience.
• Proven publication record in top conferences.
• Mentor capable and able to drive measurable business impact.

Responsabilidades

• Design and deploy semantic chunking models for lengthy legal documents.
• Build document enrichment systems using legal taxonomies.
• Develop LLM-based knowledge graph pipelines linking citations/entities.
• Lead knowledge distillation to latency-constrained, production-ready models.
• Design evaluation frameworks with expert annotation and synthetic data.
• Own architecture decisions and collaborate with engineering on scale.

Conhecimentos

Python programming

Research leadership

Mentoring

Cross-functional collaboration

NLP/Information extraction knowledge

Formação académica

PhD in Computer Science or related

Ferramentas

PyTorch

Hugging Face Transformers

DeepSpeed

Descrição da oferta de emprego

Thomson Reuters Foundation in New York seeks a Lead Applied Scientist to own design, development, and production deployment of document understanding systems powering Westlaw, PracticalLaw, and CoCounsel. You will advance semantic chunking, enrichment via legal taxonomies, and LLM-based knowledge graphs.

You will lead distillation to latency-aware models, define evaluation frameworks, and mentor a team of applied scientists while shaping AI strategy for multiple product lines.