Generative AI trainer (Experienced corporate trainer)

We are seeking a knowledgeable and passionate Freelancer Generative AI Trainer to join our team. The ideal candidate will have expertise in Generative AI technologies, specifically in Long Language Models (LLMs), and a deep understanding of the underlying mechanisms behind their functioning. This role involves training and educating teams on various aspects of Generative AI, including LLMs, common pipelines, data querying, prompt engineering, fine-tuning, challenges at the enterprise scale, knowledge graph applications, non-functional requirements (NFRs), and the comparison between on-premises and cloud-based LLM implementations. Key Responsibilities: Generative AI Overview: Deliver comprehensive training sessions on the workings of Long Language Models (LLMs) and their application in various domains. Common Pipelines Understanding: Educate on Langchain and Semantic Kernel within the common pipeline structure to enable a deep understanding of their functionalities. Utilization of Vector DBs and Embeddings: Instruct on how to effectively utilize Vector Databases and Embeddings in Generative AI applications. Querying Unstructured Data: Guide teams on querying techniques and strategies specifically tailored for unstructured data using Generative AI. Querying Structured Data: Demonstrate effective methods for querying structured data leveraging Generative AI tools and approaches. Prompt Engineering Techniques: Train on the art of prompt engineering to craft meaningful and productive interactions with LLMs. Fine-Tuning Processes: Instruct on fine-tuning models to achieve specific outcomes and improve performance in various scenarios. Enterprise-scale Gen AI Challenges: Educate on challenges and best practices when implementing Generative AI solutions at an enterprise scale. Application of Knowledge Graphs with LLMs: Demonstrate the integration and utilization of Knowledge Graphs in conjunction with Long Language Models for enhanced results. Non-Functional Requirements (NFRs) for Gen AI: Detail the necessary non-functional requirements for successful Generative AI implementation and operation. Comparison: On-prem vs. Cloud LLMs: Provide insights into the differences, advantages, and challenges of on-premises versus cloud-based LLM implementations. Requirements: Advanced degree in Computer Science, Artificial Intelligence, or related field. Proven experience in Generative AI technologies, specifically Long Language Models (LLMs). Proficiency in programming languages commonly used in AI/ML development. Strong communication and presentation skills to effectively train and educate teams. Experience in conducting workshops, seminars, or training sessions is highly desirable. Ability to translate complex technical concepts into easy-to-understand training material.