Develop end-to-end NLP and GenAI solutions, including text classification, summarization, RAG systems, conversational AI, and document intelligence pipelines. Build, fine-tune, and evaluate LLM-based models using transformer architectures (BERT, GPT, T5, LLaMA, etc.). Deploy models and AI apps using modern MLOps practices across cloud environments (Azure preferred).
Requirements
- 5–8 years of experience in data science with deep hands-on expertise in NLP and Generative AI.
- Proficient in transformer models, embeddings, and modern NLP libraries (Hugging Face, spaCy, NLTK).
- Strong Python skills with experience in PyTorch/TensorFlow for advanced model development.
- Practical experience building RAG architectures, vector search, and prompt optimization.
- Solid understanding of MLOps, model deployment, monitoring, and productionization.
- Strong problem-solving abilities with excellent communication and stakeholder engagement skills.
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