NEPAL APPLIED MATHEMATICS AND INFORMATICS INSTITUTE FOR RESEARCH
(NAAMII)
TERMS OF REFERENCE (TOR)
Position:
AI Foundation Trainers (2 open positions)
Duty Station:
Field-based, with assignments at partner colleges and universities across Nepal; base at NAAMII, Kupondole
Employment Type:
Consultancy engagement — full-time level of effort during active curriculum development and delivery periods
Reports to:
Project Manager; day-to-day coordination with the Community Manager
NAAMII is calling for AI Foundation Trainers who will skill the current workforce to transform their existing organizations to AI native organizations. The trainers will contribute to curriculum design, practical delivery and continuous improvement of a learning pathway that enables learners to understand core AI concepts, work with data and code, build responsible AI-enabled solutions, and progress towards deeper technical study or applied roles.
About the Organization
NAAMII is a profit-not-distributing AI Center of Excellence founded by Nepali researchers with a broader vision: to build a self-sustaining AI ecosystem from Nepal that can generate world-class knowledge, prepare people for a rapidly changing future, and translate AI into meaningful social and economic impact.
NAAMII builds this ecosystem through three connected pillars:
- Knowledge Generation: Advancing frontier AI research and working on high-impact problems across areas including computer vision, natural language processing, healthcare, computational genomics, climate systems, agriculture and food systems, and the social dimensions of AI. NAAMII researchers have contributed to more than 80 research publications, demonstrating that globally relevant AI research can be produced from a resource-constrained setting.
- Knowledge Dissemination: Making rapidly evolving AI knowledge understandable and useful across education, government, industry and society. Through initiatives such as the Annual Nepal AI School, which has trained more than 2,500 participants from over 40 countries, NAAMII helps people not only adapt to an AI-enabled world but also build the confidence and capability to contribute to it.
- Translation and Innovation: Turning research and talent into real-world value through industry R&D, startup building and incubation. NAAMII has supported the incubation of three startups and contributes evidence and expertise to wider conversations on responsible AI, policy and governance.
A central challenge within this ecosystem is learning. As AI reshapes jobs, institutions and sectors, conventional education cannot respond through lectures or one-time tool demonstrations alone. People need learning experiences that help them understand AI, apply it to real problems, question its outputs and continue adapting as technologies change. The curriculum follows a problem-based learning model, where learners build evidence of their capabilities as they progress by solving real-world problems. Their learning is validated against competency models, enabling them to develop and demonstrate practical, hands-on skills.
NAAMII’s approach is grounded in the AI Pyramid, a conceptual framework that recognises that AI capability is not one-size-fits-all.1 AI Native provides the broad baseline: the confidence, judgment and responsible habits needed to reason and work effectively with AI. AI Foundation develops the technical and role-specific capability to work with data, code, models and AI-enabled workflows, while AI Deep prepares advanced learners to conduct frontier research and develop new methods. The pyramid is not a ladder that everyone must climb; rather, it represents the different and interdependent levels of capability needed across society and the workforce.
About the Project
The UDAAN (Unleashing Digital Acceleration and Ambition of Nepali Youth) project, led by Youth Innovation Lab together with Heifer Project Nepal, NAAMII, and Women In Animation and supported by the European Union, is a nationwide initiative aimed at empowering young women and men across Nepal with the skills, opportunities, and resources needed to thrive in the digital economy.
Implemented over four years, the project focuses on advancing digital literacy, fostering innovation and entrepreneurship, and creating pathways to employment through training programs in AI, coding, and creative technologies, as well as internships, fellowships, and innovation hubs in partnership with local governments, academic institutions, and the private sector.
With a strong commitment to gender equality and social inclusion, UDAAN prioritizes marginalized and underrepresented youth, contributing to a more inclusive, resilient, and future-ready workforce in Nepal. The action is implemented through four interconnected components:
1. PATHSHALA - Digital Skills Development: Builds future-ready digital skills through AI, Coding, and Animation schools. Using tiered, hybrid learning, it prepares young Nepali women and men for jobs, innovation, and entrepreneurship in the digital economy.
2. KARYASHALA - Innovation and Experimentation: Transforms youth skills into real-world digital solutions through hackathons and bootcamps. It nurtures innovation with mentorship and incubation, turning ideas into scalable impact.
3. KARMASHALA - Employment and Career Pathways: Connects young Nepali youth to real-world work experience through internships and fellowships. It bridges skills to careers by placing youth in government and private sector roles, building employability and professional confidence.
4. NITISHALA - Policy and System Strengthening: Strengthens youth participation in digital governance through policy dialogues, innovation hubs, and civic engagement. It bridges youth, communities, and local governments to institutionalize inclusive and sustainable digital transformation.
Position Summary
NAAMII is calling for an AI Foundation Trainer - Educational Institutions to help learners move from basic AI awareness to practical technical capability. This is not only a classroom-delivery role. The trainer will contribute to designing and improving the AI Foundation curriculum, facilitate hands-on learning in programming, data, machine learning and responsible AI, and guide learners to build solutions around real academic, institutional and community problems. Through UDAAN and other NAAMII initiatives, the trainer will work with partner colleges and universities, support learners from varied technical backgrounds, connect theory with practice, and bring evidence from delivery back into the continuous improvement of the curriculum, pedagogy and wider AI learning ecosystem.
Key Responsibilities
A. Shape the AI Foundation Learning Experience
- Contribute to the design, review and continuous improvement of the AI Foundation curriculum, modules, practical exercises, assessments and trainer resources.
- Translate core concepts in programming, data, machine learning and responsible AI into clear, structured and engaging learning experiences.
- Use learner performance, institutional feedback and emerging technical developments to keep the pathway relevant and rigorous.
B. Redesign Technical Learning Through Practice
- Move learning beyond lectures towards hands-on coding, experimentation, collaborative problem solving and project-based learning.
- Help learners connect technical concepts with real challenges from education, research, institutions, communities and industry.
- Create a learning environment where learners can test ideas, debug, reflect, ask questions and build confidence through practice.
C. Facilitate Applied and Responsible AI Development
- Guide learners in using standard programming, data and AI tools to explore datasets, build basic models, evaluate outputs and develop practical prototypes.
- Help learners understand model limitations, data quality, bias, privacy, ethics and responsible development practices.
- Adapt examples and projects to different academic disciplines while maintaining the technical quality and intended learning outcomes of the AI Foundation framework.
D. Build Learner Capability and Progression
- Support learners with varied levels of mathematics, programming and prior exposure to AI through structured guidance and differentiated support.
- Guide learners through practical activities, assignments, assessments and projects using Tangible, approved coding environments and other learning tools.
- Help learners build the confidence and foundation needed to apply AI in their discipline, pursue advanced learning, or progress towards AI-enabled roles.
E. Strengthen the AI Foundation Model
- Capture learner feedback, common misconceptions, technical barriers, successful projects and emerging learning needs from each cohort.
- Document evidence of learner participation, technical progression, project completion and practical application, together with required attendance and assessment records.
- Work with NAAMII curriculum, research, programme and institutional teams to improve the content, pedagogy, delivery model and transition between AI Native, AI Foundation and AI Deep learning pathways.
F. GESI, Accessibility and Safeguarding
- Create an inclusive, respectful and gender-responsive technical learning environment in which women, marginalized groups and learners with different levels of prior access can participate confidently.
- Adapt facilitation, examples, pacing and learner support to reduce barriers related to language, disability, digital access, technical confidence and previous educational opportunity.
- Promote safe and responsible participation, protect learner wellbeing and privacy, and follow NAAMII and UDAAN safeguarding, GESI and ethical AI standards throughout design, delivery and assessment.
Required Qualifications
- Bachelor's or Master's degree in computer science, artificial intelligence, data science, software engineering, mathematics, statistics, education technology, or a closely related field.
- Strong understanding of programming fundamentals, data handling, machine learning concepts and responsible AI, with the ability to explain them clearly to learners.
- At least 2 years of experience in teaching, technical training, curriculum development, mentoring, software or data science or AI-related project work.
- Practical proficiency in Python and commonly used data science or machine learning tools and environments.
- Strong facilitation and communication skills; fluency in Nepali and working proficiency in English.
Preferred Qualifications
- Experience designing or delivering courses in programming, data science, machine learning, AI or related technical subjects.
- Experience with project-based learning, assessment design, learning platforms, Git-based workflows or cloud/notebook environments.
Submission Requirements
- Latest CV/Resume: Attach a PDF copy of your most recent CV or resume.
- Cover Letter: Submit a cover letter explaining your first-hand experience relevant to the role and why you believe this position is the best fit for you. Please avoid duplicating information already included in your CV or resume. The cover letter should be no more than one page.
- Financial proposal with daily rates and Full-time (month) fee in local currency i.e. NPR.
- One-Minute Video: Submit a one-minute video explaining your interest in the role and what motivates you to apply.