SCOPE OF THE MISSION:

The intern will design and implement LLM pipelines integrating RAG techniques, agentic AI, and vector databases to enhance knowledge retrieval and interaction capabilities. These pipelines will be applied to various projects, including the development of intelligent chatbots, task-specific AI assistants, and other interactive NLP applications. The role involves experimenting with state-of-the-art models, optimizing performance, and ensuring scalability for real-world use cases. Main tasks

QUALIFICATIONS:

• Currently pursuing a degree in Data Science, Computer Science, Engineering, or a related field.
• Strong understanding of Machine Learning algorithms and NLP techniques.
• Proficiency in programming languages such as Python or R.
• Experience with data analysis and visualization tools (e.g., Pandas, NumPy, Matplotlib).
• Familiarity with NLP libraries and frameworks (e.g., spaCy, NLTK, Hugging Face Transformers).
• Knowledge of Retrieval-Augmented Generation (RAG) techniques.
• Knowledge of Generative AI models (e.g., GPT, BERT).
• Experience with vector databases and knowledge bases.
• Familiarity with cloud technologies is appreciated (Azure or AWS).
• Excellent problem-solving skills and attention to detail.
• Ability to learn quickly and adapt to a fast-paced environment.
• Strong communication and teamwork abilities.

• Collaborate with the Data Science and Engineering team to design, develop, and implement Machine Learning models for NLP and Generative AI projects.
• Conduct research on the latest advancements in NLP and Generative AI to enhance project outcomes.
• Develop and fine-tune models for tasks such as text generation, sentiment analysis, and language understanding.
• Assist in the deployment and monitoring of models in a production environment.Participate in team meetings and contribute to project planning and strategy discussions.