[Hiring] NLP Engineer @BigStep Technologies Pvt Ltd

Role Description

We are hiring a hands-on NLP Engineer to build robust pipelines that convert policy, regulatory, fintech, and healthcare documents into structured, graph-ready data. You will own the full extraction lifecycle from raw text to clean, schema-validated outputs using classical NLP, deep learning, and LLM APIs.

Qualifications

• 3–5 years hands-on NLP engineering & real production pipelines, not just model experiments
• Strong Python skills: OOP, async programming, packaging, and testing
• NLP frameworks: spaCy, HuggingFace Transformers, NLTK
• Deep learning: fine-tuning transformer models for sequence labeling and classification
• LLM API integration: prompt engineering, structured outputs, and function/tool calling
• Data pipeline experience: ETL, batch processing, and text pre-processing at scale
• JSON schema design and validation using pydantic or json schema

Requirements

• Pipeline Development: Design and build end-to-end text extraction pipelines for policy, regulatory, fintech, and healthcare 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: Leverage LLM APIs with structured output extraction, prompt engineering, and tool/function calling
• Data Engineering: Build scalable Python pipelines for high-volume document processing with robust pre-processing for PDF, DOCX, and HTML
• Schema & Graph Readiness: Define and enforce JSON schemas; ensure outputs are clean and compatible with knowledge graph ingestion
• Accuracy Improvement: Evaluate model performance, track metrics, and implement feedback loops to improve extraction quality over time

Benefits

• Experience with legal, regulatory, or policy documents (contracts, compliance filings, government publications)
• Familiarity with knowledge graphs or graph databases (Neo4j, RDF)
• Document parsing tools: pdfplumber, Docling, Apache Tika
• Domain knowledge in fintech or healthcare NLP
• Exposure to information extraction benchmarks (CoNLL, DocRED, SciERC)