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Description: The intern will contribute to the design and development of deep learning and generative AI models in NLP and Computer Vision areas to solve real-world problems across domains such as education, healthcare etc. Responsibilities include data collection, preprocessing, algorithm selection, model training, fine-tuning, and integration into applications. The role may also involve building Retrieval-Augmented Generation (RAG) applications using LLMs, enhancing solutions with domain-specific context retrieval. Role may require working with image data as well.

Required Skills: Foundational knowledge of Machine Learning, Deep Learning and NLP. Working experience with ML libraries such as TensorFlow, PyTorch, or Scikit-learn. Exposure to Generative AI concepts and tools (e.g., GPT, LLaMA, Claude). Familiarity with RAG architectures and their implementation is a strong plus.

Traits: Eagerness to learn and work with cutting-edge AI technologies. Ability to work both independently and collaboratively. Strong problem-solving and communication skills.

Expected Outcomes: Design and development of Deep Learning and NLP models addressing industry-specific use cases.

Specific courses required for project execution: Machine Learning, Deep Le

WILP - Center of Excellence in Artificial Intelligence and Machine Learning

Station Overview

Project 1

Title: Applied AI Intern