Master Trainer Artificial Intelligence

Company name- Anudip Foundation For Social Welfare

Website- www.anudip.org

Location- Madhya Pradesh (Bhopal)

Responsibilities:

1. Train-the-Trainer Delivery & Faculty Enablement

• Design and deliver structured TtT sessions that build both AI subject knowledge and facilitation skills.
• Certify and onboard faculty against a defined competency framework before they deliver to learners.
• Conduct live demonstrations, model teaching sessions, and guided practice-teach-back exercises.
• Provide ongoing coaching, feedback, and refresher sessions to maintain delivery standards.
• Train and certify faculty at partner colleges to deliver the Google DeepMind AI curriculum within their own institutions.

2. Curriculum Contextualisation & Content Development

• Translate the Google DeepMind course content into structured, delivery-ready lesson plans, facilitator guides, labs, and assessments.
• Develop trainer toolkits, model answers, rubrics, and capstone project briefs.
• Simplify complex AI and ML concepts into learner-friendly formats suitable for diverse, first-generation learners.

3. Academic Quality & Program Alignment

• Monitor session quality through classroom observation, sample audits, and learner feedback.
• Align curriculum, projects, and assessments with entry-level AI-enabled job roles and current hiring trends.
• Support faculty screening and technical interviews for the AI program.
• Report progress, competency data, and quality metrics in line with program and CSR/donor requirements.

Technical Competency Requirements

Must-Have :

• AI & Machine Learning Foundations
• Solid grasp of core ML concepts: supervised/unsupervised learning, model training, evaluation, and neural network basics.
• Ability to explain how modern AI systems (including deep learning and transformers) work at a conceptual level.
• Generative AI & Applied Tools
• Hands-on experience with LLMs and generative AI tools (e.g., Google Gemini) and structured prompt engineering.
• Practical use of Python and Google Colab for AI demonstrations and applied exercises.
• Responsible AI
• Understanding of AI safety, fairness, bias, transparency, and data-ethics, with the ability to teach these practically.
• Training & Instructional Skills
• Proven Train-the-Trainer / faculty-development capability and strong facilitation skills.
• Experience in curriculum design, lesson planning, and assessment development.

Good-to-Have

• Exposure to deep learning frameworks (TensorFlow / PyTorch) or DeepMind-related learning resources.
• Familiarity with reinforcement learning or notable AI applications (e.g., AlphaFold-type case studies) for teaching context.
• Relevant certifications in AI/ML, Generative AI, or Google AI/Cloud credentials.
• Experience delivering programs in CSR, NGO, or skilling environments for diverse learners.

Illustrative Projects the Trainer Should Be Able to Deliver & Mentor

• A prompt-engineered AI assistant / chatbot built using Gemini for a real-world use case.
• A simple ML classification or prediction model demonstrated end-to-end in Colab.
• A Responsible-AI case study: identifying and mitigating bias in a given scenario.
• A capstone project brief and rubric that faculty can run with their own learner cohorts.

Qualifications & Experience:

• Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, IT, or a related discipline.
• Minimum 2+ years of practical experience in AI/ML delivery, technical training, or curriculum development, with strong hands-on Generative AI skills.
• Prior Train-the-Trainer, faculty-mentoring, or facilitation experience preferred.
• Relevant AI/ML or Generative AI certifications are an added advantage.
• Experience in CSR, NGO, or government skilling initiatives is an added advantage.