About the role
Interview Kickstart is a premier career transformation platform turbocharging tech careers through AI upskilling.
Founded in 2014 in Santa Clara by Soham Mehta, ex-Box Engineering Leader, and Ryan Valles, a transformative P&L leader and former CEO with a track record of scaling ventures, Interview Kickstart’s vision is to help every tech professional thrive in today’s fast-evolving tech industry.
With 40+ domain-specific courses—from foundational Machine Learning and Generative AI to Agentic AI, System Design, and DSA—Interview Kickstart equips engineers, PMs, data professionals, and tech leaders to accelerate their careers. Its 600+ instructors—industry practitioners, hiring managers, and senior engineers from FAANG+ companies—bring real-world insight and cutting-edge expertise into every classroom.
Beyond upskilling, Interview Kickstart offers end-to-end career support. Personalized mock interviews, resume and LinkedIn branding, career coaching, salary negotiation guidance, and performance-based job referrals ensure that your AI upskilling translates into real career breakthroughs. Over 25,000 professionals have already advanced their careers through Interview Kickstart.
Recognized by TIME x Statista and GSV 150 as a top EdTech company, Interview Kickstart is the go-to platform for tech professionals looking to future-proof their careers in the age of AI.
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
Originally posted on Himalayas