About NASCA

NASCA is one of India’s premier educational content research organisations, widely recognised for its pioneering work in STEM / STEAM education and skill development programmes across leading schools and institutions in India. NASCA’s mission is to integrate cutting-edge technology education into school curricula and empower students with future-ready 21st-century skills in areas such as Artificial Intelligence, Electronics, Robotics, Design Thinking, Coding, and other industry-relevant domains. NASCA’s programmes are aligned with the National Education Policy (NEP) 2020 and the ATL Mission.

NASCA is also a privileged content collaborator with the International Baccalaureate Organization (Geneva) and is recognised by KHDA (Dubai).

Role Overview

NASCA is seeking a highly competent and academically strong Artificial Intelligence Subject Matter Expert who can design, develop, and lead AI education programmes for K-12 schools and Higher Education institutions. The selected candidate will play a central role in drafting NASCA’s comprehensive AI curriculum, creating grade-wise and level-wise learning modules, mentoring teachers, conducting faculty training, and directly teaching AI-led programmes at NASCA partner institutions. The role requires strong practical knowledge of Artificial Intelligence, Machine Learning, Generative AI tools, Python programming, AI/ML software platforms, and emerging digital technologies.

Working knowledge of Electronics, Arduino, Robotics, IoT, or physical computing will be an added advantage, especially for integrating AI with hands-on STEAM projects.

Position : AI Faculty & Curriculum Development

Location : Mumbai

Nature of Employment : Full-Time salaried employment

Educational Qualifications

- M.Tech / M.E. / M.Sc. / MCA / PhD in Artificial Intelligence, Machine Learning, Data Science, Computer Science, Information Technology, Electronics, Robotics, Mechatronics, or allied technology domains.
- Strong academic background from reputed institutions will be preferred.
- Certifications in AI, ML, Data Science, Python, Cloud AI platforms, Generative AI, Prompt Engineering, or related areas will be an added advantage.

Key Responsibilities 1) AI Curriculum Research, Design & Development

- Conceptualise, draft, and continuously upgrade a comprehensive Artificial Intelligence curriculum for K-12 and Higher Education programmes.
- Develop structured AI learning pathways across Foundation, Preliminary, Intermediate, and Advanced levels, ensuring progression from basic digital literacy to practical AI/ML application development.
- Create age-appropriate AI modules for students ranging from Junior KG to Grade 12, and advanced modules for undergraduate / higher education learners.
- Draft application-based AI projects that translate theoretical concepts into hands-on learning experiences and real-life problem-solving activities.
- Integrate Artificial Intelligence, Machine Learning, Generative AI, Python, Data Analytics, Coding, Design Thinking, IoT, Robotics, and Electronics wherever relevant to create interdisciplinary STEAM learning outcomes.
- Develop grade-specific lesson plans, project manuals, teacher guides, student activity sheets, worksheets, rubrics, assessments, and instructional presentations, including audio-visual learning content.

2) AI,



ML & Generative AI Content Expertise

- Design curriculum content covering AI fundamentals, machine learning concepts, supervised and unsupervised learning, neural networks, computer vision, natural language processing, prompt engineering, responsible AI, data ethics, and practical AI tool usage.
- Create learning modules using Python and relevant AI / ML libraries and platforms such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow / Keras, OpenCV, Jupyter Notebook / Google Colab, Teachable Machine, and other learner-friendly tools.
- Research and incorporate latest Generative AI tools and workflows, including text generation, image generation, AI assistants, prompt-based learning, no-code / low-code AI platforms, and classroom-secure AI productivity tools.
- Ensure the curriculum balances conceptual understanding, hands-on experimentation, project development, ethical usage, creativity, and practical applicability for school and college learners.

3) Alignment with School and Higher Education Programmes

- Map NASCA’s AI curriculum with individual school curricula and higher education programme requirements to ensure academic consistency and seamless institutional integration.
- Align learning outcomes with NEP 2020, ATL Mission objectives, skill development priorities, interdisciplinary project-based learning, and future-readiness expectations.
- Customise AI learning modules for different boards, institutional contexts, age groups, learning levels, and student capabilities.
- Ensure the AI curriculum supports inquiry-based, experiential, interdisciplinary, and application-oriented pedagogy.

4) Teacher Mentoring, Faculty Training & Capacity Building

- Mentor NASCA faculty members and partner school teachers to effectively implement AI, ML, GenAI, Python, and STEAM-based curriculum modules.
- Conduct regular teacher training, orientation, and upskilling sessions to build institutional capability and ensure long-term academic self-sufficiency among partner schools and institutions.
- Prepare teacher training manuals, implementation notes, demonstration videos, assessment guides, and classroom delivery support material.
- Provide academic guidance to faculty members, monitor performance, resolve content-delivery challenges, and ensure consistent delivery standards aligned with NASCA’s educational vision and pedagogical framework.

5) Teaching, Demonstration & Institutional Delivery

- Deliver AI and technology sessions directly at NASCA partner schools, colleges, and institutions as required.
- Conduct demonstration classes, masterclasses, workshops, student bootcamps, faculty development programmes, and academic orientation sessions.
- Simplify complex AI and ML concepts for students and teachers across varied age groups, academic backgrounds, and learning levels.
- Support student innovation projects, AI prototypes, competitions, innovation expos, and project showcases.

6)



Academic Quality Control & Programme Implementation

- Conduct periodic quality review visits to partner institutions to monitor implementation efficacy, classroom delivery, teacher readiness, student engagement, and learning outcomes.
- Review curriculum implementation data, teacher feedback, student project quality, assessment outcomes, and institutional requirements to recommend corrective actions and improvements.
- Maintain high academic documentation standards, including version-controlled curriculum files, lesson plans, assessments, project repositories, and implementation reports.
- Present curriculum designs, AI programme updates, pedagogical innovations, and implementation insights at academic management meetings, client schools, institutional reviews, and business development discussions.

Professional Experience

- Minimum 4-6 years of experience in Artificial Intelligence, Machine Learning, Data Science, Computer Science, EdTech, technology education, or curriculum development.
- Minimum 2 years of experience in mentoring teachers, training faculty teams, managing academic delivery teams, or leading technology learning programmes.
- Prior experience with EdTech companies, reputed schools, colleges, universities, skill development organisations, or technology training institutions will be preferred.
- Demonstrated experience in creating curriculum, lesson plans, project manuals, classroom presentations, assessments, and teacher training material.
- Hands-on experience in delivering AI / ML / Python / GenAI sessions to school students, college learners, teachers, or professional learners.

Expected Skill Set and Personal Attributes

- Strong subject matter expertise with the ability to simplify complex AI and ML concepts for learners across different age groups.
- Excellent written and verbal communication skills in English, with the ability to draft professional curriculum documents, presentations, training notes, and academic reports.
- Strong teacher mentoring, classroom delivery, presentation, and workshop facilitation skills.
- High analytical thinking, quick information processing, and ability to research emerging AI tools and convert them into structured learning modules.
- Team player with excellent interpersonal skills, people management ability, and maturity to work with school leadership, teachers, parents, students, and internal academic teams.
- Adaptable and capable of multitasking across curriculum development, faculty training, teaching, academic reviews, and institutional presentations.
- Passionate about technology education, disciplined in documentation, and committed to high academic standards.
- Strong belief in inquiry-driven, hands-on, project-based, interdisciplinary pedagogy.

Key Deliverables

- Comprehensive AI curriculum framework for K-12 and Higher Education programmes.
- Grade-wise and level-wise AI / ML / GenAI learning modules with clear learning outcomes.
- Teacher guides, lesson plans, student activity sheets, project manuals, assessments, and rubrics.
- Faculty training and teacher mentoring plans with measurable implementation outcomes.
- Institution-ready AI workshops, bootcamps, masterclasses, and demonstration classes.
- Quality review reports, curriculum improvement notes, and implementation feedback summaries.

📌 AI Instructor (Mumbai)
🏢 NASCA
📍 Mumbai