We are seeking a highly motivated and knowledgeable No-Code AI & Machine Learning Trainer to deliver a practical, hands-on program that enables students to design, build, and deploy AI / ML solutions using no-code and low-code platforms. The trainer will bridge theory with practice, empowering students to implement machine learning, computer vision, NLP, and automation workflows without writing complex code.
Key Responsibilities
- Deliver engaging sessions on AI / ML fundamentals and no-code tools such as Obviously.ai, Peltarion, Teachable Machine, and DataRobot.
- Conduct hands-on training on data preparation, model building, and deployment using cloud-based platforms (Google AutoML, Azure ML Studio).
- Guide students through real-world AI use cases including predictive analytics, chatbots, computer vision, and workflow automation.
- Mentor students in capstone projects—from dataset preparation to model deployment and presentation.
- Train students on AI app development using Bubble, Glide, and AppSheet.
- Introduce AI ethics, explainability, and responsible AI principles through case discussions and activities.
- Support academic coordinators in assessment design, progress tracking, and project evaluations.
- Stay current with emerging no-code AI tools and best practices to ensure industry relevance.
Technical Expertise Required
No-Code ML Platforms : Obviously.ai, Peltarion, Levity.ai, Teachable Machine, DataRobotAutoML Tools : Google AutoML, Azure ML Studio, AWS Sagemaker CanvasData Tools : Airtable, Retool, Datawrapper, Google SheetsNo-Code App Builders : Bubble, Glide, AppSheetChatbot Builders : Dialogflow, Voiceflow, LandbotAutomation Tools : Zapier, Make (Integromat), Power AutomateDomains Covered : Machine Learning, Computer Vision, NLP, Predictive AnalyticsCloud Platforms : GCP, Azure, AWS (for AutoML and deployment)Preferred Qualifications
Bachelor’s / Master’s Degree in Computer Science, Artificial Intelligence, Data Science, or related field.3–8 years of experience in AI / ML development, workflow automation, or data science education.Experience in teaching, mentoring, or corporate training (especially in no-code / low-code platforms).Strong understanding of machine learning concepts, including model evaluation, ethics, and deployment.Familiarity with AI integrations via APIs and automation workflows.