Prior experience building and deploying LLM or agent-based applications in real-world settings
Strong proficiency with agent frameworks like LangGraph, CrewAI, or LangChain
Strong understanding of system design principles, especially in AI/ML-based architectures
Demonstrated ability to explain complex technical topics to diverse audiences
Experience teaching, mentoring, or creating content for working professionals in tech
Excellent communication and collaboration skills, with a learner-first mindset
Bonus: Contributions to open-source AI projects, publications, or prior experience with AI upskilling programs
Responsibilities:
Instruction Delivery: Conduct lectures, workshops, and interactive sessions to teach machine learning principles, algorithms, and methodologies. Instructors may use various teaching methods, including lectures, demonstrations, hands‑on exercises, and group discussions.
Industry Engagement: Staying current with the latest trends and advancements in machine learning and related fields, engaging with industry professionals, and collaborating on projects or internships to provide students with real-world experiences.
Research and Development: Conducting research in machine learning and contributing to developing new techniques, models, or applications.
Constantly improve the session flow and delivery by working with other instructors, subject matter experts, and the IK team.
Help the IK team in onboarding and training other instructors and coaches
Have regular discussions with IK’s curriculum team in evolving the curriculum.
Should be willing to work on weekends/evenings and be available as per the Pacific time zone Demo Guidelines for Agentic AI