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Job Description
Structured overview of role & requirementsAbout This Role
Conduct research and implementation of advanced techniques such as Retrieval-Augmented Generation (RAG) to enhance language model capabilities.
Assist with data preparation, fine-tuning pipeline setup, quantization, and training of small transformer models focusing on performance and efficiency.
Support development of internal orchestration frameworks, integration of LLM software components, deployment, and monitoring of AI models in production environments.
Minimum Requirements
Proficiency in Python programming.
Experience in data wrangling and preprocessing.
Familiarity with LangChain, LlamaIndex, VectorDB, and understanding of transformer architectures and related ML frameworks (TensorFlow or PyTorch).
Work Experience Required: Student-level internship, no prior full-time experience explicitly required.
Ideal Candidate Profile
Comfortable working on cutting-edge AI/ML research and engineering tasks related to large language models.
Ability to collaborate with senior engineers in integrating complex AI systems into existing architectures.
Strong technical foundation in transformer models, embeddings, tokenizers, fine-tuning and deployment processes.