Hire Iris G. - AI Researcher

Responsible for de-risking R&D initiatives related to explainable AI and machine fault detection. - Demonstrated end-to-end ownership by researching, developing and deploying an LLM powered chat application that recommends and extracts knowledge from explainable AI tools, serving as a “talk to your model” application. - Designed and implemented a bespoke recommender system and retrieval augment generation (RAG) pipeline, parameterized and monitored using a lightweight MLOps framework. - Shared ownership of the team's explainable AI (XAI) library, translating high level research literature of leading edge explainable AI methods into highly performant python implementations.

* Conceptualized and implemented data science strategies to achieve high-level business and research objectives. Collaborated cross functionally to build an internal MLOps platform using Kubeflow - Spearheaded data science and engineering work to develop and productionize data science pipelines for various client and internal projects, delivering core product features on time and within budget, while managing expectations through proactive communication and regular progress updates - Researched, developed, and deployed an edge Machine Learning (ML) model to predict breast cancer with 92% accuracy and >98% sensitivity for a medical device client. - Innovated a bespoke facial emotion recognition model that outperforms off-the-shelf solutions from AWS and Google