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

Requirements

7+ years building and deploying ML systems in production, with recent experience in generative AI and LLMs
Strong understanding of ML fundamentals, model fine-tuning, and evaluation methodologies
Experience building production AI systems - you understand latency, cost optimization, and evaluation challenges
Proficient in Python and ML frameworks (PyTorch, TensorFlow, HuggingFace, etc.)
Thrive in high-agency, high collaboration cultures

Benefits

Professional development
Remote work options

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learninggenerative AIlarge language modelsmodel fine-tuningevaluation methodologiescontent moderation systemsAI model developmentdynamic interfacessemantic searchknowledge graphs

Soft Skills

collaborationhigh-agency culture