AI Intern

We are looking for a highly motivated and tech-savvy AI Intern to join our AI team and assist in cutting-edge projects involving large language models (LLMs), Retrieval Augmented Generation (RAG), image generation, and fine-tuning tasks. This is a fantastic opportunity to work under the mentorship of experienced AI engineers and gain hands-on experience with advanced AI stacks including Mistral, LLAMA, AWS Bedrock, and Virtual Try-On models like CatVTON.

Key Responsibilities:
• Support the training and fine-tuning of large language models (LLMs) for businessspecific use cases.
• Assist in instruction fine-tuning and dataset preparation, including cleaning, augmentation, and annotation.
• Help develop and test Retrieval-Augmented Generation (RAG) pipelines and contribute to multi-agent RAG architecture experiments.
• Contribute to image layering and virtual try-on models, particularly in assisting with data input and output validation.
• Participate in research on emerging tools such as Mistral AI, LLAMA, and Bedrock, and document findings.
• Collaborate with the AI team to run experiments, monitor model performance, and adjust hyperparameters.
• Design and implement Model Context Protocols (MCPs) to define input/output formats, memory scopes, tool usage boundaries, and conversation guidelines for LLM agents.
• Document code, pipelines, and research outcomes clearly and effectively.
• Stay up to date with AI advancements and propose small-scale experiments based on recent papers or trends.

Qualifications:
• Pursuing or recently completed a Bachelor’s/Master’s degree in Computer Science, AI/ML, Data Science, or a related field.
• Strong understanding of machine learning fundamentals and deep learning concepts.
• Familiarity with Python and libraries such as PyTorch, TensorFlow, Transformers, or LangChain.
• Exposure to LLMs or RAG pipelines (even via projects or coursework) is a big plus.
• Understanding of agent frameworks and prompt engineering is a bonus.
• Comfortable working with Jupyter notebooks, Git, and cloud environments (AWS/GCP/Azure).
• Curious, fast learner, and enthusiastic about building real-world AI solutions.

What You’ll Gain:
• Exposure to production-level AI workflows and tools.
• Mentorship from a Senior AI Engineer working on bleeding-edge tech.
• Real-world experience with LLMs, RAG, MCPs, image models, and model deployment.
• Opportunity to publish internal research, contribute to demos, or develop portfolio-worthy projects.
• A collaborative, hands-on learning environment that bridges theory and practice.