Jolie Blake

I’m a PhD scientist and award-winning educator applying AI-driven systems—especially LLM-powered applications, retrieval-augmented generation (RAG), and NLP classification—to improve learning experiences. I analyze performance data to identify failure patterns and translate findings into targeted workflow improvements.

In my Advanced STEM AI Data Trainer role at Invisible Technologies, I evaluate AI model outputs in chemistry and mathematics, using structured rubrics and data-informed critique to refine accuracy and behavior. Earlier, my postdoctoral work in product engineering and metrology improved throughput by 15% and reduced projected production costs by 20% through data-driven redesign.

I build user-facing AI tools that are scalable and reliable, from RAG chatbots (ChromaDB + sentence-transformers) to emotion detection and real-time image captioning (BLIP). I’m currently pursuing an IBM Generative AI Engineering Certification (in progress, expected July 2026) to deepen how I engineer effective AI pipelines for real-world learning needs.