GenAI Trainer | Full-time

Generative AI (Gen AI) Trainer

Key Responsibilities

• Curriculum Design & Delivery

  : Develop and deliver comprehensive training modules on

  Generative AI, Large Language Models (LLMs), and AI/ML fundamentals

  , ensuring content is current with industry trends.

• Hands-On Training

  : Conduct interactive sessions covering

  Prompt Engineering, Natural Language Processing (NLP), LangChain, RAG (Retrieval-Augmented Generation), OpenAI APIs, Hugging Face tools

  , and other Gen AI applications.

• Project Guidance

  : Mentor learners through capstone projects, including the design and deployment of AI-powered applications.

• Assessment & Feedback

  : Evaluate student progress with assignments, assessments, and one-on-one feedback to ensure learning outcomes are met.

• Collaboration

  : Work with KIT Skill Hubs academic team to refine course materials, incorporate the latest AI advancements, and maintain training quality.

• Continuous Learning

  : Stay updated with emerging trends in Generative AI, LLM architectures, and cloud-based AI services to keep the curriculum cutting-edge.

Required Skills and Qualifications

• Proven experience as an

  AI/ML Trainer

  , Data Scientist, or AI Engineer with direct exposure to

  Generative AI

  technologies.
• Strong proficiency in

  Python

  and AI/ML libraries such as

  TensorFlow, PyTorch, scikit-learn, and Hugging Face Transformers

  .
• Hands-on experience with

  LLMs (e.g., GPT, Falcon, LLaMA)

  ,

  LangChain

  ,

  prompt engineering

  , and building RAG-based applications.
• Solid understanding of

  NLP

  , data preprocessing, and deployment of AI models.
• Familiarity with

  cloud platforms

  (AWS, Azure, or GCP) and model hosting services.
• Excellent communication, presentation, and mentoring skills to explain complex concepts clearly to a diverse audience.
  
• Bachelor’s or Master’s degree in

  Computer Science, Artificial Intelligence, Data Science

  , or a related field.

Preferred Qualifications

• Industry certifications in AI/ML or cloud technologies (e.g., AWS AI/ML, Azure AI Engineer).
• Experience in developing and deploying AI-driven applications in production environments.
• Prior experience conducting corporate or classroom training programs.