Role Overview
Develop and deploy NLP solutions using transformers, text mining techniques, and modern language models. Build production-ready systems for text analysis and understanding.
Responsibilities
- Design and implement NLP pipelines for text classification, entity recognition, and information extraction
- Build transformer-based models for various NLP tasks and applications
- Develop text mining solutions to extract insights from large-scale unstructured data
- Implement and customize spaCy pipelines for domain-specific NLP requirements
- Integrate and fine-tune LLMs for text processing and understanding tasks
- Optimize NLP models for performance, accuracy, and production deployment
- Collaborate with data scientists and engineers to deliver end-to-end NLP solutions
Requirements
- Bachelor's degree in Computer Science, Computational Linguistics, AI/ML, or related field
- Strong expertise in transformer architectures (BERT, RoBERTa, T5, GPT)
- Proven experience with text mining and information extraction techniques
- Proficiency in spaCy for NLP pipeline development
- Hands-on experience working with LLMs and their applications
- Strong Python programming skills
- Experience with Hugging Face Transformers library
- Understanding of NLP fundamentals (tokenization, embeddings, semantic analysis)
Preferred
- Experience with named entity recognition (NER), sentiment analysis, and text classification
- Knowledge of traditional NLP techniques (TF-IDF, word embeddings, POS tagging)
- Familiarity with NLTK, Gensim, or other NLP libraries
- Experience with model fine-tuning and transfer learning
- Understanding of multilingual NLP and cross-lingual models
- Knowledge of MLOps and model deployment pipelines
- Experience with document processing and OCR integration
