- 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.).
- Design and implement custom NLP workflows, embeddings, semantic search, vector databases, and prompt engineering strategies.
- Develop scalable advanced ML models leveraging deep learning, traditional ML, and hybrid architectures.
- Deploy models and AI apps using modern MLOps practices across cloud environments (Azure preferred).
- Collaborate closely with product, engineering, and business teams to translate requirements into AI-driven solutions.
- Monitor model performance, conduct error analysis, and continuously optimize pipelines.
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