Problem Setter & Technical Content Intern

About this role

About the role: - Write and develop learning content for Scaler's Full Stack Development, AI/ML, and Data Science programs alongside business-to-business projects - Design programming exercises, coding assignments, competitive contests, and reference cards spanning full stack, backend, artificial intelligence, and machine learning domains - Develop and improve AI-powered interview simulations used across the platform's programs - Review problem sets created by fellow team members to guarantee quality and an engaging learning experience - Work alongside content creators to generate new ideas and help shape the direction of Scaler's educational materials What you'll work on: - Testing and validating technical problems to ensure they meet learning objectives and provide clear feedback - Crafting clear, precise explanations and editorial content that make complex concepts accessible - Iterating on AI interview systems to improve their effectiveness and realism - Contributing to brainstorming sessions that define content priorities and strategy - Building a portfolio of educational materials across multiple technology stacks What we're looking for: - Graduating in 2025 or later - Codeforces rating of 1600 or above, CodeChef rating of 5★ or higher, or demonstrable equivalent competitive programming background - Deep grasp of data structures, algorithms, discrete mathematics, and foundational computer science - Hands-on experience with Java and Spring Framework, or Python and Django - Publicly visible GitHub profile showcasing real-world or academic projects - Ability to explain technical concepts clearly in writing and conversation - Background with large language models, prompt design, or AI agent systems (advantageous but not required)