About: Simplilearn
Simplilearn is the world’s #1 online Bootcamp provider, enabling learners around the globe with rigorous and highly specialized training offered in partnership with world-renowned universities and leading corporations. We focus on emerging technologies and skills, such as data science, cloud computing, programming, and more — that are transforming the global economy. Our training is hands-on and immersive, including live virtual classes, integrated labs and projects, 24x7 support, and a collaborative learning environment. Over two million professionals and 2000 corporate training organizations across 150 countries have harnessed our award-winning programs to achieve their career and business goals.

Simplilearn has collaborated with Full stack Academy to leverage its widespread footprint in the US region and partnerships with Top US universities to grow internationally

Job Summary

We are seeking experienced Generative AI Trainers to deliver live online training sessions covering modern generative models, LLMs, LangChain, RAG, and prompt engineering with hands-on demos and projects.

Key Responsibilities

• Deliver live, instructor-led online classes
• Conduct hands-on demos, guided practices, and projects
• Explain concepts using real-world use cases
• Address learner queries and ensure engagement
  

Required Skills & Expertise

Generative AI & Foundation Models

• Generative AI model types and applications
• VAEs and GANs (architecture, use cases, limitations)
• Transformer-based models and attention mechanisms
• Self-attention and multi-head attention
  

Language Models & LLMs

• Language models fundamentals and applications
• Large Language Models (architecture, training, operations, types)
  

Retrieval-Augmented Generation (RAG)

• RAG concepts, components, retrievers, and workflows
• Real-world applications of RAG
  

LangChain

• LangChain architecture and core components
• Building applications using LangChain
• Prompt, memory, chains, and model integration
• Text generation pipelines with Hugging Face models
  

Prompt Engineering

• Prompt fundamentals and optimization
• Zero-shot, few-shot, CoT, Self-Consistency, ToT prompting
• Prompt templates and LangChain prompts
• Prompt engineering applications (data & synthetic data generation)
  

Model I/O & Data Handling

• Model I/O (prompts, LLMs, output parsers)
• Document loaders (CSV, PDF, HTML, JSON, Markdown)
• Text splitters and embeddings in GenAI
  

Qualifications

• 10+ years of experience in Generative AI / NLP / LLMs
• Strong proficiency in Python, LLM frameworks, and LangChain
• Prior online or classroom training experience