Harshwardhan Raghunath Harsh Patil
Machine Learning Engineer @Upper Hand
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WORK HISTORY
Machine Learning Engineer @Upper Hand
Indianapolis, IN, US
Developing Terraform Scripts for managing infrastructure on GCP.• Leading Lift and Shift migration from Heroku to GCP with estimated savings up to 60%.• Leading the development of ETL and ELT pipelines in GCP. • Leading the development of pipeline orchestration platform on GCP.• Reduced Fivetran expenses by 40% and Deepnote expenses by 60%. • Owned dashboard development for 4 enterprise clients, collaborating with stakeholders to design KPI-driven visualizations that directly generated in MRR. • Automated marketing KPI reporting using Fivetran, PostgreSQL, and Metabase, tracking metrics such as CTR, CPC, and engagement rate. Reduced manual reporting time by 80% and enabled monthly performance reviews with leadership.• Developed Quickbooks library to fetch Profit and Loss (Accural and Cash-Basis) data for 2 clients with 10+ locations.• Visualized financial dashboards to analyze revenue, expenses, royalties, and AP/AR across 6 business units, including 3 years of MoM and YoY trends, generating in MRR and delivering actionable financial insights. • Integrated U.S. Census demographic data by zip code into business intelligence workflows, contributing an additional in ARR.
EDUCATION
Shivaji University, Kolhapur
Bachelor of Technology - BTech, Computer Science
Indiana University Bloomington
Master of Science - MS, Computer Science
ABOUT HARSHWARDHAN RAGHUNATH HARSH PATIL
I am a Machine Learning Engineer focused on designing and operating production-grade, end-to-end ML systems on Google Cloud Platform.I am leading the development of ML workflows spanning data modeling, feature engineering, training, deployment, and monitoring. I work primarily with Python, PyTorch, BigQuery, PostgreSQL, Docker, Terraform, REST APIs, and GitHub. I have also delivered analytical dashboards to meet client and business needs.I approach problems with first-principles thinking: focusing on system boundaries and failure modes before selecting models or architecture. Beyond hands-on development, I own architectural decisions for ML systems and Data Pipelines, review designs and code, and help define standards for model development and ML infrastructure. I regularly mentor engineers, lead knowledge transfer sessions, and raise the quality bar across performance, cost efficiency, and long-term maintainability.I am currently looking to grow into senior-level machine learning roles where I can continue to have impact through technical leadership, system design, and mentorship.Outside of work, I enjoy playing Chess, Making DIY Diaries, and Doing Origami.
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