Key Responsibilities
- Design, build, and deploy NLP models for intent classification, named entity recognition (NER), and sentiment analysis using traditional methods (BiLSTM, TF-IDF) and modern frameworks
- Implement and optimize Large Language Models (LLMs) and Generative AI to enhance dialogue management and agent capabilities
- Lead the development and optimization of conversational systems using Rasa NLU
- Drive end-to-end development from proof-of-concept to production-ready systems, including API deployment
- Conduct design reviews, define technical standards, and mentor junior engineers
- Establish evaluation frameworks to measure model quality, accuracy, and safety
Requirements
- 7+ years of professional experience in AI/ML engineering
- 5+ years of hands-on experience with Python, including object-oriented programming and clean, testable code
- 3+ years of experience with BiLSTM, TF-IDF classifiers, and word embeddings (Word2Vec, GloVe)
- 2+ years of experience with Rasa NLU and Rasa Core
- Strong proficiency in ML frameworks: PyTorch or TensorFlow