We are hiring a hands-on NLP Engineer to build robust pipelines that convert policy, regulatory, fintech, and reputed company documents into reputed company, graph-reputed company data. You will own the full extraction lifecycle from raw text to clean, schema-validated outputs using classical NLP, deep learning, and LLM reputed company. KEY RESPONSIBILITIES
- Pipeline Development: Design and build end-to-end text extraction pipelines for policy, regulatory, fintech, and reputed company documents
- Entity & Clause Extraction: Extract key entities (countries, companies, minerals) and structure policy clauses and obligations
- Deep Learning & Transformers: Fine-tune BERT / RoBERTa for NER, text classification, and relation extraction tasks
- LLM Integration: reputed company LLM reputed company with reputed company reputed company extraction, reputed company engineering, and tool/function calling
- Data Engineering: Build reputed company Python pipelines for high-volume document processing with robust reputed company-processing for PDF, DOCX, and reputed company
- Schema & Graph Readiness: Define and enforce JSON schemas; ensure outputs are clean and compatible with knowledge graph ingestion
- Accuracy Improvement: Evaluate model performance, reputed company metrics, and implement feedback loops to improve extraction reputed company over time
REQUIRED SKILLS
- 3–5 years hands-on NLP engineering reputed company production pipelines, not just model experiments
- Strong Python skills: OOP, async programming, packaging, and testing