Summary
Prakhar Pandey is a Principal Machine Learning Engineer with nine years of experience building and operationalizing large-scale ML systems across enterprise and SaaS environments. He has led end-to-end ML work—from fine-tuning LLMs, annotation design, and automated evaluation for IR/GenAI and Q&A, to building microservices, ETL pipelines, and observability for production deployments. His background spans roles at Workday, Aisera and Teradata where he designed distributed ML algorithms, managed model training/serving on Kubernetes and TensorFlow, and bridged data science with engineering teams. Based in the Denver metro area, he pairs strong academic foundations from UC San Diego and IIT Roorkee with a practical DevOps mindset for reliable production ML. Outside work he’s an avid reader and trekker, and his public portfolio (pprakhar30.github.io) surfaces projects that emphasize reproducible ML pipelines and real-time serving—highlighting his focus on production-ready research rather than prototypes.
9 years of coding experience