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Preferred Qualifications:
● 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
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Interview Kickstart

Interview Kickstart

Interview Kickstart