• Design, build, and deploy machine learning models in production environments • Develop classification systems to automatically categorize educational content by subject, grade level, and learning standards • Build and maintain computer vision pipelines (e.g., object detection, OCR, image segmentation) for worksheet and student-submission analysis • Design and implement RAG (Retrieval-Augmented Generation) systems using large content libraries • Engineer and optimize prompts for AI-generated educational content and assessment validation • Build AI-driven quality assurance systems to evaluate generated content against educational taxonomies • Develop agentic AI workflows that iteratively refine and improve generated outputs • Deploy and operate AI services on AWS, ensuring scalability, reliability, and cost efficiency • Collaborate directly with client stakeholders and cross-functional engineering teams • Define and, when required, contribute to data labeling or feedback strategies supporting model quality • Maintain clear documentation for models, pipelines, and AI system behavior • Participate in code reviews and promote AI engineering best practices