Role Overview
We are looking for a curious, hands-on AI Researcher to design and develop MethdAI's learning modules in Artificial Intelligence, Machine Learning, and Robotics for Grade 6–12 students. The role is research and curriculum-development focused — you will build structured, project-based modules that run on Raspberry Pi and other edge devices, making real-world AI tangible and accessible for school students across our partner network.
Key Responsibilities
- Research, design, and develop age-appropriate learning modules covering Computer Vision, NLP, Machine Learning, and Edge AI for Grades 6–12, with clear scaffolding across difficulty levels.
- Build and test all hands-on activities, experiments, and mini-projects on Raspberry Pi (and compatible hardware such as Arduino, Coral USB Accelerator, or Jetson Nano, where applicable).
- Develop working code templates, datasets, and guided notebooks for each module — using block-based tools (Scratch, ML4Kids) for junior grades and Python for senior grades.
- Create educator guides, student workbooks, assessment rubrics, and setup documentation for each module to enable smooth in-school delivery.
- Research and evaluate tools, libraries, and lightweight models (OpenCV, TensorFlow Lite, Teachable Machine, Whisper, etc.) suitable for deployment on edge devices in low-resource school environments.
- Iteratively improve modules based on pilot feedback from partner schools and MethdAI educators.
- Collaborate with the MethdAI content and delivery team to ensure modules are classroom-ready and aligned with the overall learning framework.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Electronics, Robotics, AI/ML, or a related discipline.
- Hands-on experience with Raspberry Pi — setting up environments, running Python scripts, interfacing with cameras, sensors, and peripherals.
- Working knowledge of AI/ML fundamentals (supervised/unsupervised learning, CNNs, NLP pipelines, model evaluation) and experience deploying lightweight models on edge devices.
- Proficiency in Python and familiarity with libraries such as OpenCV, scikit-learn, TensorFlow Lite, PyTorch, or Hugging Face Transformers.
- Experience or strong interest in K–12 STEM education, curriculum design, or instructional technology — ability to translate complex technical concepts into structured, student-friendly learning experiences.
- Strong documentation and technical writing skills for creating clear guides, notebooks, and workbooks.
Good to Have
- Prior experience developing or delivering robotics or AI programs for school students.
- Familiarity with block-based AI tools (ML4Kids, Teachable Machine, Scratch AI extensions).
- Exposure to tools like Coral Edge TPU, ONNX Runtime, or MediaPipe for optimised edge inference.
- Understanding of AI safety and responsible AI principles for age-appropriate framing.
What You'll Build
Learning modules across four core tracks — Computer Vision (object detection, image classification), NLP (text classification, speech recognition), Machine Learning (regression, classification, clustering), and Edge AI (model optimisation, on-device inference on Raspberry Pi) — packaged as ready-to-deploy classroom kits for schools.
