Instructor, Gen AI, Simplilearn (Part time)

Fullstack Academy, Inc.; United States; On-site; USD 56,826 - 80,934; Part time

Job summary

A leading online education provider is seeking experienced Generative AI Trainers to deliver impactful online training sessions. The role involves conducting live classes that include hands-on demos and addressing learner queries to ensure engagement. Ideal candidates should have over 10 years of experience in Generative AI and demonstrate strong proficiency in Python and relevant frameworks. This part-time position offers competitive compensation of $50 per hour, with an expected workload of 8-10 hours per week.

Qualifications

• 10+ years of experience in Generative AI / NLP / LLMs.
• Proven expertise in LLM frameworks and LangChain.
• Experience in delivering training, either online or in-person.

Responsibilities

• Deliver live, instructor-led online classes.
• Conduct hands-on demos and guided practices.
• Engage learners by addressing queries.

Skills

Generative AI model types and applications

Strong proficiency in Python

Prior online or classroom training experience

Transformer-based models and attention mechanisms

RAG concepts and workflows

Prompt fundamentals and optimization

Tools

LangChain

Job description

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

Compensation:

Part‑Time Instructors are hourly, non‑exempt employees. As such they will be compensated for all time worked. Part‑time Instructors can expect to work approximately 8‑10 hours per week and should not exceed expected hours without manager approval.

The expected compensation for this role for candidates is $50 per hour for candidates who fulfill the qualifications for the role.