anyone-ai - Academic Program Lead, AI Fellowship
Requirements
• Experience designing or owning technical curricula for AI/ML fellowships, intensive programs, universities, corporate academies, or equivalent environments. • Teaching experience in university courses, fellowships, bootcamps, corporate academies, or similar settings, including lecturing, facilitating, or leading technical cohorts. • Hands-on AI/ML experience in industry or applied research. • Experience interviewing or evaluating technical instructors, experts, or educators and maintaining a high standard for delivery. • Comfortable working in a dynamic environment with fast iteration and a high degree of ambiguity. • PhD in a technical field such as Computer Science, Machine Learning, or a related STEM discipline, or equivalent deep technical expertise in AI. • Proven hands-on experience working with AI/ML, preferably in industry. • Strong teaching and content-development skills, including the ability to create clear slides, rigorous exercises, and substantive technical projects. • Fluent in Spanish and English.
Responsibilities
• CURRICULUM & LEARNING DESIGN • Own the fellowship syllabus, including learning objectives, curriculum sequencing, and how individual modules fit together to produce meaningful, practical skill development. • INDUSTRY-ALIGNED CONTENT • Oversee the team responsible for designing learning content, including slides, exercises, projects, and supporting materials. Ensure the curriculum stays current with AI industry practices, technological developments, and hiring demand. • PROGRAM QUALITY • Set and maintain the quality standard across all learning materials and program experiences. Review learner outcomes and delivery feedback and continuously improve the curriculum based on those signals. • INSTRUCTOR NETWORK • Help source instructors from Anyone AI’s network, interview and evaluate candidates, and brief and calibrate instructors so classroom delivery consistently meets the curriculum standard. • TECHNICAL & ACADEMIC LEADERSHIP • Act as the internal reference for what high-quality AI education should look like. Partner closely with program operations to ensure logistics and delivery decisions support—not dilute—the learning experience.
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