• Implement, test, and deploy LLM-powered conversational agents that understand complex user queries, provide accurate and relevant responses, and adapt to diverse conversational contexts.
• Integrate and manage diverse data sources (structured and unstructured) to enhance the knowledge base and contextual understanding of conversational AI models.
• Adapt pre-trained language models to our specific domain and use cases.
• Experiment with different fine-tuning techniques to improve model performance on relevant tasks.
• Evaluate model performance using appropriate metrics and iterate on training strategies.
• Implement RAG Architecture
• Integrate existing generative models with structured and unstructured data using RAG techniques.
• Develop and optimize retrieval mechanisms to identify relevant information from the knowledge data efficiently.
• Refine the generation process to produce coherent and informative responses based on retrieved knowledge.
• Skills
• Strong understanding of RAG architecture and its applications.
• Proficiency in Python and relevant deep learning frameworks (e.g., PyTorch, TensorFlow).
• Experience with information retrieval techniques and tools, including relational and NoSQL databases.
• Ability to work independently and as part of a team
• Ability to work in a fast-paced, customer-focused startup environment
• Ability to pivot and adapt to changing requirements

AI Developer - The AI Developer is an experienced software developer specializing in artificial intelligence and machine learning technologies. This role collaborates closely with the Software Architect (R&D) to research, design, and implement innovative AI/ML solutions that align with future architectural standards. The AI Developer explores new algorithms, frameworks, and tools to create intelligent systems that support and enhance business objectives, contributing to the organization s technology roadmap and setting the foundation for advanced, data-driven capabilities

C#, TensorFlow, Python, Java Script