Rider Ledez

- Architected and implemented advanced NLP models for medical text classification, improving claims processing automation by 30% through enhanced accuracy.
- Fine-tuned Large Language Models (LLMs) using Hugging Face Transformers and GPT, leading to improved patient engagement solutions and automated responses.
- Enhanced semantic search capabilities with Retrieval-Augmented Generation (RAG) techniques, resulting in a 25% increase in information retrieval efficiency.
- Collaborated with cross-functional teams to design and deploy scalable ETL pipelines using Spark and Snowflake, ensuring high-quality data for model training.
- Mentored junior engineers on best practices for model development and deployment, fostering a culture of continuous learning and innovation.
- Developed chatbot solutions using RLHF, significantly reducing support response times by 40% and improving user interaction.
- Conducted time-series forecasting to predict patient appointment trends, optimizing resource allocation and improving operational efficiency.
- Utilized AWS and Azure for deploying machine learning models, streamlining MLOps processes and enhancing deployment efficiency.