Manikantareddy Duggempudi

I am excited to apply for the AI / Machine Learning Engineer position. With over 3 years of experience designing and deploying end-to-end AI systems in healthcare and enterprise domains, I bring a proven ability to translate advanced research into scalable, cloud-based solutions that deliver measurable impact. At CitiusTech, I led the development of clinical AI workflows using LangGraph and LLaMA-based models to power intelligent medical assistants and analytics chatbots. By integrating these systems with AWS and FHIR-based data sources, I reduced manual data extraction by 50% and optimized model inference latency by 30% through vLLM deployment and GPU-aware scaling. I also implemented Guardrails AI and AWS Secrets Manager for HIPAA-compliant RAG pipelines, reducing PII exposure by 40%. Previously, at Happiest Minds Technologies, I engineered predictive patient segmentation, OCR, and defect detection systems using TensorFlow, PyTorch, and SageMaker, achieving up to 94% accuracy and automating more than 40 hours of manual work weekly. I also built end-to-end ML orchestration pipelines with FastAPI and MLflow, ensuring seamless retraining, versioning, and continuous monitoring. I will complete my Master's in Information Technology and Management from the University of North Carolina in December 2024, equipping me with advanced expertise in LLM fine-tuning, MLOps automation, and cloud-native AI design. I am eager to leverage these skills to drive innovation and deliver scalable AI solutions that align with your organization's mission. Thank you for considering my application. I would welcome the opportunity to discuss how my background and experience can contribute to your team's success.