Harinath Reddy Yelampalle

Results-driven AI Developer with over 4 years of experience in designing and deploying cutting-edge machine learning, deep learning, and NLP solutions to drive operational efficiency and innovation. Proficient in Python, TensorFlow, PyTorch, and Hugging Face Transformers. Proven track record of optimizing AI pipelines by reducing model training time by up to 35% and increasing accuracy by over 20% in diverse applications, such as insurance claim prediction and conversational AI. Spearheaded scalable deployments on AWS, Google Cloud, and Vertex AI with a 99.9% reliability rate. Generated $2.1M in cost savings through advanced feature engineering and real-time analytics. Led teams in developing voice-enabled AI agents and chatbots, resulting in a 25% increase in user engagement and a 45% reduction in customer service workloads. Adept at leveraging Retrieval-Augmented Generation (RAG), prompt engineering, and cloud-native tools like Docker to build context-aware and impactful AI solutions. Passionate about pushing the boundaries of generative AI and computer vision. Holds a Master's in Business Analytics with a GPA of 3.62 and maintains a robust portfolio on GitHub.

• Boosted insurance claim prediction accuracy to 91%, cutting processing time by 25% and saving $2.1M via ML pipeline on Vertex AI.
• Developed a voice-enabled AI for Hulk Fitness, reducing response time by 30% and increasing engagement by 25%.
• Led a restaurant chatbot project, slashing customer service workload by 45% with 92% satisfaction using Lang Flow API and RAG.
• Slashed model training time by 35% and maintained 98% accuracy, deploying 15+ ML models at TechRobots Inc.
• Enhanced sentiment analysis, processing 1M+ feedback entries monthly with 22% fewer errors and 45% better efficiency.
• Designed scalable AI agents with LangChain and Hugging Face, achieving 92% satisfaction through advanced prompt engineering.