• Collaborate with researchers to perform research operations using existing infrastructure • Use judgment in complex scenarios and help apply standard techniques to a wide variety of technical problems • Characterize neural network quality, failure modes, and edge cases based on research data • Maintain awareness of current trends in relevant areas of research and technology • Coordinate with researchers and accurately convey status of experiments • Manage a large number of concurrent experiments and make accurate time estimates with respect to deadlines • Review experimental results and suggest theoretical or process improvements for future iterations • Write technical reports indicating qualitative and quantitative results to external parties

• Collaborate with researchers to perform research operations using existing infrastructure • Use judgment in complex scenarios and help apply standard techniques to a wide variety of technical problems • Characterize neural network quality, failure modes, and edge cases based on research data • Maintain awareness of current trends in relevant areas of research and technology • Coordinate with researchers and accurately convey status of experiments • Manage a large number of concurrent experiments and make accurate time estimates with respect to deadlines • Review experimental results and suggest theoretical or process improvements for future iterations • Write technical reports indicating qualitative and quantitative results to external parties

• Design, debug, and maintain ML systems in realistic, tools-enabled environments • Work across training, evaluation, and infrastructure to ensure ML systems behave correctly and robustly in practice

• Design and build evaluation systems that assess educational AI quality across thousands of conversations - from learning outcomes to bias detection to curriculum alignment • Build ML systems that enable self-improving app creation - learning from high-quality apps on the platform to automatically scaffold new applications for educators • Design and prototype downloadable, on-device AI models that work without internet connectivity - critical for privacy and global accessibility • Develop systems that enable dynamic, fluid interfaces adapting to learning moments - transitioning seamlessly from chat to writing editor to interactive physics simulation as needed • Build content moderation and safety systems designed specifically for educational discourse • Implement agentic AI systems that enable educators to create goal-directed applications (e.g., "help students through this project over 2 weeks") • Build sophisticated RAG systems that integrate diverse educational content with semantic search and knowledge graphs