• Strong, hands-on ML foundations: you’ve trained, evaluated and shipped models yourself (scikit-learn, PyTorch or TensorFlow).
• The ability to explain the “why” behind ML clearly to engineers new to it.
• Excellent spoken and written English. All courses are scripted, narrated and delivered in English, so you need clear, natural, easily understood English and confidence on camera.
• A genuine passion for teaching, shown through courses, tutorials, talks, workshops or mentoring you’ve done because you enjoy it.
• Current with the field and keen to keep learning.
• Clear, engaging spoken English and confidence on camera.
• Openness to an established teaching methodology and to editorial feedback.
• Published online courses, a book, or university/bootcamp teaching experience.
• Experience with fine-tuning, MLOps or deploying models in production.
• Cloud ML certifications (AWS, Azure, GCP, Databricks).
• Send your CV or LinkedIn profile, plus a link that shows how you teach: a course, a talk, a tutorial or a short video.