About Me
I’m Jayashree Ramesh Reddy, a Data Science graduate student at the University of Memphis, specializing in designing end-to-end machine learning and AI systems. My work focuses on building scalable data pipelines, developing high-performance models, and optimizing workflows for production environments. I work extensively with Python, SQL, and modern ML frameworks to architect systems that efficiently process, transform, and analyze complex structured and unstructured datasets.
My technical expertise spans supervised and unsupervised learning, deep learning, NLP, and LLM engineering. I build and fine-tune advanced models using Scikit-learn, TensorFlow, PyTorch, and Hugging Face Transformers, with hands-on experience in LLM fine-tuning (LoRA/QLoRA), embedding generation, vector databases (FAISS, Chroma), and RAG architectures. I work with tokenization, attention mechanisms, optimizers, evaluation metrics, and model interpretability techniques, and I systematically profile and optimize models for performance, latency, and memory efficiency.
I also work with cloud and big-data technologies—such as AWS, Databricks, Snowflake, and Apache Spark—to build scalable data pipelines, distributed processing workflows, and production-grade ML deployments. My interest lies in aligning traditional ML systems with modern generative AI, integrating RAG pipelines, vector search, and prompt-optimized inference to create robust, reliable, and high-impact AI applications. I’m driven by building technically sound, scalable, and efficient solutions that deliver measurable value in real-world environments.
Name: Jayashree Ramesh Reddy
Email: jayashreeramesh2409@gmail.com
From: Memphis, United States
Education: Masters in Data Science
