Curriculum developer

Job Title: Curriculum Developer Employment Type: Full-Time Experience Required: Minimum 2 years Availability: Immediate Location : Remote About Sustainable Living Lab (SL2) Sustainable Living Lab (SL2) was founded in Singapore in 2011 with the aim of developing impactful, sustainable solutions in line with the UN’s Sustainable Development Goals. Our clients include several Governments, international development organizations, leading MNCs, and SMEs. Our expertise is in utilizing technology as a lever for sustainability and applying a community-driven approach for implementation. We have a strong presence in Asia with teams in Singapore, Indonesia, India, and the US. About the Program SL2 develops and implements a suite of digital literacy and skilling programs aimed at empowering people to use technology impactfully and responsibly in the AI-fueled world. We work with multiple stakeholders from a global technology giant to India’s largest IT consultancy & premier academic institutions. The program aims at bridging the digital divide by: Imparting skills to both technical/ non-technical audiences in the field of AI Empowering students with not just technical skills but also career growth skills and soft skills to ensure lifelong relevancy in the workforce of the future Reaching 30 million people, in partnership with 30 countries About the Role We’re seeking a Subject Matter Expert for AI learning content creation. The curriculum is aimed at diverse groups of audiences. An ideal candidate must have a passion for good teaching content and intermediate Python coding experience. Responsibilities: Plan, create, and maintain course curricula covering Artificial Intelligence, Machine Learning, Data Science, Io T, Python programming and cutting-edge AI domains (Generative AI, Agentic AI, and Multimodal AI) for diverse audiences (K–12 students, college learners, and workforce professionals) across global contexts Develop instructor-led training (ILT) materials, including detailed facilitator guides, lesson plans, and classroom activities that support live teaching Design learning experiences optimized for instructor delivery, balancing conceptual explanations, discussions, demonstrations, and hands-on practice Define clear and measurable learning objectives and outcomes Design lesson architectures grounded in credible research, ensuring alignment with current pedagogical best practices and accessibility standards Write, maintain, and test Python code examples and interactive code notebooks  Conduct quality checks (QC) of content and  incorporate feedback from internal reviews, validator feedback, or pilots to improve curriculum effectiveness Requirements: Minimum 1 year of working experience with creating educational content (i.e., lecturer, university teaching assistant, facilitator) – preferably with previous teaching experience Strong conceptual understanding of core AI/ML algorithms and techniques Awareness of recent advancements in AI, with the ability to translate these into educational content, including:  Generative AI: algorithms and model architectures (e.g., transformers, diffusion models, GANs), training and fine-tuning approaches, prompt design, evaluation methods, and applied use cases Agentic AI: understanding autonomous AI agents, task orchestration, tool use (e.g., APIs, external knowledge sources), agent libraries and frameworks (eg., Lang Graph and Auto Gen), reasoning workflows, Model context protocol (MCP) for agent interactions Multimodal AI: approaches that integrate text, image, audio, and other modalities for real-world applications Willingness and ability to continuously learn and adapt to emerging AI technologies and frameworks in a rapidly evolving space Intermediate-level knowledge of Python Experience in using Python libraries such as Num Py, Pandas, Scikit-Learn, Matplotlib, and Keras Familiarity with CRISP-DM / Data Science Project Cycle Familiarity with Google Colab, Jupyter Notebook, and tools such as Microsoft Office and Google Suite Should be able to show projects developed in Python (i.e., Git Hub repo)