Data Scientist

We are seeking a skilled and innovative Data Scientist to join our team, specializing in the development of AI agents, Retrieval-Augmented Generation (RAG) models, and cutting-edge technologies like LangChain and OpenAI. This is a hands-on role where you will leverage large language models (LLMs) to build intelligent systems that can handle complex tasks and provide actionable insights. You will work alongside engineers and product teams to design, deploy, and optimize AI models that integrate both structured and unstructured data. Key Responsibilities: AI Agent Design & Development: Design and develop intelligent AI agents using OpenAI GPT models, LangChain, and other advanced LLMs (e.g., GPT-4, future models like Gemini and Llama). Implement and optimize multi-agent systems that leverage RAG (Retrieval Augmented Generation) techniques to access and utilize external data sources for enhanced agent performance. Collaborate with the engineering team to build AI agents capable of completing complex tasks autonomously. Machine Learning & Model Development: Develop, train, and fine-tune machine learning models for various applications, including natural language processing (NLP), text generation, and reinforcement learning. Implement RAG frameworks to enable models to retrieve and incorporate real time contextual information from external data stores (e.g., FAISS, Pinecone). Design and deploy LLM-based solutions for various business problems, optimizing them for efficiency and accuracy. Data Preparation & Feature Engineering: Clean, preprocess, and transform large datasets from both structured (SQL/NoSQL) and unstructured (text, documents, etc.) sources. Engineer features that improve model performance, particularly in the context of AI agents and LLMs. Develop data pipelines that support continuous updates to the agents knowledge base and ensure that agents have access to up-to-date information. Collaboration & Cross-Functional Support: Work closely with data engineers, product managers, and business teams to define project goals, build solutions, and integrate AI models into the company's product offerings. Communicate technical results and insights clearly to stakeholders, providing actionable recommendations based on data-driven insights. Research & Innovation: Stay up-to-date with the latest advancements in AI, NLP, machine learning, and RAG techniques. Explore and experiment with emerging AI frameworks like LangChain, OpenAI API, and others to improve model performance and capabilities. Contribute to R&D efforts to develop novel AI solutions and enhance the current system.