* Design, implement, test, and continuously optimize end-to-end RAG pipelines, including data parsing, ingestion, prompt engineering, and chunking strategies.
* Curate and develop high-quality datasets, using synthetic data generation for robust training and evaluation.
* Rigorously evaluate LLM applications on various metrics including correctness, latency, and hallucination.
* Assist in the deployment of LLM-based applications, analyze user feedback, and contribute to iterative improvements.
* Write clean, maintainable, and testable code following best practices.
* Collaborate with cross-functional teams to integrate AI components into other systems.
Requirements:
* Master or Ph.D. in Computer Science, Machine Learning, or a related field and a minimum of 2 years of hands-on industry experience in software engineering.
* Expertise and intensive hands-on experience in LLM/RAG development.
* Strong skills in Python framework SentenceTransformers and data analysis libraries (Pandas, NumPy).
* Hands-on experience with vector databases (e.g., Chroma) and RAG evaluation frameworks.
* Strong communication and presentation skills.