Applied Scientist, NLP/GenAI
Tasks
- Advance research through publications
- Build document enrichment systems
- Design AI models for document understanding
- Develop knowledge graph pipelines
- Evaluate model performance
- Optimize models for efficiency
- Partner with engineering teams
- Translate legal document challenges into solutions
Perks/Benefits
- Career Development Programs
- Community engagement
- Flexible work arrangements
- Hybrid work model
- Impact in Legal and Information Sectors
- Industry Benefits
- Mental health support
- Volunteer days
Skills/Tech-stack
Data Generation | Deep learning | Document processing | Entity recognition | Graph construction | Hierarchical Taxonomy Handling | Information Extraction | Knowledge Distillation | Knowledge Graph Construction | Knowledge graph | Language Models | Language Processing | Large Language Models | Legal document processing | Machine Learning | Multi-document Reasoning | Natural Language | Natural Language Processing | Programming | Question Answering | Relation extraction | Retrieval systems | Semantic chunking | Synthetic Data Generation | Synthetic data | Text Classification
Education
AI | Doctorate in Computer Science | Master's in Computer Science | NLP
Roles
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