Summary
Arunbh Yashaswi is a data scientist and graduate assistant with eight years of experience building production-grade ML and automation systems across healthcare and cloud-native environments. He has driven high-impact projects—ranging from a multi-modal document understanding pipeline that boosted structure recognition to 96% accuracy to a serverless incident response system that cut console logins by 80%—and consistently focuses on turning notebooks into operational services. Comfortable with transformers, ONNX/PyTorch optimization, LLM prompt engineering, and event-driven architectures on Azure and AWS, he combines model fine-tuning with pragmatic MLOps to reduce costs and deployment time. Notably, he built LLM-powered failure analysis and self-service remediation workflows embedded in Slack, demonstrating an eye for developer experience as well as reliability. Based in College Park, MD, he’s pursuing an MS in Data Science at UMD while bringing a track record of scaling document processing and automated remediation in production.
8 years of coding experience
3 years of employment as a software developer
Bachelor of Technology, Bachelor of Computer Science, Bachelor of Technology, Bachelor of Computer Science at Vellore Institute of Technology
Master of Science - MS, Data Science, Master of Science - MS, Data Science at University of Maryland
ISC - CISCE, Science, ISC - CISCE, Science at Calcutta Public School - India