Ishesh Murarka
Principal Software Engineer @ Amazon | AI Skeptic turned Evangelist | Distributed Systems & ML at Scale (100M+ Customers) | Building 0-to-1 Products
- Role
- Principal Engineer at Amazon
- Location
- Seattle, WA, US
- LinkedIn followers
- 500 followers
About Ishesh Murarka
With over a decade of experience, I bring a deep expertise in large-scale system architecture, machine learning solutions, and technical strategy. As a Principal Engineer at Amazon, I lead a team of 180+ engineers within the Customer Fulfillment organization, dedicated to delivering innovative solutions that enhance customer experience and drive operational efficiency. Passionate about building scalable systems, I thrive in collaborative environments that value innovation and continuous improvement to tackle complex challenges and create meaningful impact. At Amazon, I spearheaded the development of a Local Catalog System that localized 100MM+ offers across multiple countries, driving significant savings in shipping costs and improving customer satisfaction. Additionally, I led the technical strategy for a highly successful LLM chatbot for product troubleshooting, achieving an impressive resolution rate of over 80%. My focus remains on leveraging technology to optimize operations and deliver tangible results for the organization.
Experience
Principal Engineer
Apr 2019 — Present · Seattle, WA, US
GenAI Leadership: Spearheaded the GenAI transformation across the organization, embedding LLM capabilities into customer support and operational decisioning.* AI Product Innovation: Launched an LLM-based chatbot using RAG and KNN lookups, achieving an 80% resolution rate for product troubleshooting.* Regional Fulfillment Platform: Architected Amazon’s first platform for intelligent inventory placement and localized delivery optimization.* Cost Efficiency: Developed a multi-objective delivery efficiency signal that resulted in over $300MM in annualized shipping cost savings.* Data Warehouse Scaling: Scaled a petabyte-sized platform to run double the workload at the same infrastructure cost via tiered architecture.* Abuse Detection: Partnered with ML scientists to productionize real-time inference models for detecting bad actors in delivery and return workflows.
Education
B. M. S. College of Engineering
Bachelor of Engineering, Information Science and Engineering
2005 — 2009
SSMRV PU College
PUC, Physics, Chemistry, Mathematics, Computer Science
2003 — 2005
Skills
- Java
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