Develop and implement advanced machine learning and deep learning models with a focus on large language models (LLMs) to solve complex NLP challenges

Use tools and frameworks such as Hugging Face, LangChain, and custom API designs to build, train, and optimize machine learning models for scalable and high-performance applications

Apply RAG techniques to improve model performance by integrating external data sources and working with vector databases for enhanced context-aware generation

Integrate OpenAI APIs, Gemini APIs, and other relevant technologies to augment model capabilities and enhance natural language understanding and generation

Stay up-to-date with the latest advancements in NLP, machine learning, and deep learning to ensure the development of cutting-edge, efficient solutions

Focus on model optimization, fine-tuning, and performance enhancement for practical deployment in real-world applications

Collaborate with cross-functional teams to design, implement, and deploy LLM-based solutions, ensuring detailed documentation for future reference and knowledge sharing

Develop and implement machine learning and deep learning models with a focus on large language models (LLMs)

Utilize tools and frameworks such as Hugging Face, LangChain, and API Design to build and optimize models

Apply Retrieval-Augmented Generation (RAG) techniques and work with vector databases

Integrate OpenAI APIs, Gemini APIs, and other related technologies to enhance model functionality

Stay current with the latest advancements in natural language processing (NLP) and machine learning (ML) to maintain cutting-edge solutions

Bachelor's degree in Computer Science/ Graduation or Post Graduate

Minimum 2 Years