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.

1. 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.

1. 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 solid 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.

📌 Master Trainer – Artificial Intelligence (Bhopal)
🏢 Anudip Foundation
📍 Bhopal