Naveen Tumkur Ramesh Babu

About Naveen Tumkur Ramesh Babu

With over eight years of software engineering experience, I am a passionate and skilled professional who strives to deliver high-quality solutions for complex and challenging problems. My mission is to leverage artificial intelligence and cloud computing to create innovative and scalable products that enhance user experience and satisfaction. I am currently working as a senior software engineer at LinkedIn, where I am part of the Ads Delivery Optimization team.In my current role, I work on various features and enhancements for the Ads delivery optimization product, which aims to improve the return on investment and efficient budget utilization for advertisers. I use Java, Scala, Python, Machine Learning, Deep Learning, and Spark to implement and optimize online and offline algorithms for LinkedIn Audience Network and Combined Marketplace. I also collaborate with cross-functional teams and stakeholders to propose and evaluate new ideas and solutions. I have contributed to multiple projects that have improved the performance and quality of the Ads delivery system.

Experience

1. Senior Software Engineer

   Linkedin

   Mar 2022 — Present · Sunnyvale, CA, US

   Optimize ad delivery at scale to maximize advertiser ROI and platform revenue—serving 10B+ daily requestsacross LinkedIn’s $15B+ ads ecosystem Designed and implemented multi-day lifetime pacing and partition-level lifetime pacing algorithms to optimizecampaign delivery and improved budget utilization Dayparting Feature (Full-Stack Ownership): Enables advertisers to schedule campaigns by day/hour, optimizingdelivery timing and budget eciency enabling $155M revenue uplift. Architected and delivered end-to-endDayparting feature: Defined Avro schemas with timezone-aware UTC conversion, built Core RESTful APIs forCRUD operations, modified pacing, projected spend logic and implemented time-window based charging/costadjustment algorithms in RCharge Spark jobs. Developed Phoenix tracking integration and LAN ranking optimizations to improve o-platform Ad delivery and10% lift in click-through rates. Event Ads optimization: Reduced under-delivery by implementing adaptive pacing for auto-bidding, improvingadvertiser ROI by 12-15% and achieving 100% budget utilization. Architected and deployed unbiased Budget Split Testing (BST) across 4 ad products (DBO CampaignGroup,Sponsored Messages, CTV, In-App), enabling data-driven budget optimization and A/B testing at scale Led cross-functional initiatives with Product, Engineering, and AI/ML teams delivering multiple optimizationfeatures/quarter on distributed systems handling 10B+ Ad requests/dayTech Stack: Java, Scala, Python, Apache Spark, Machine Learning, Kafka, REST APIs, Avro, Distributed Systems

Education

• The Ohio State University

  Doctor of Philosophy - PhD (Discontinued), Computer Science

  2019 — 2020

• The Ohio State University

  Master's degree, Computer Science

  2017 — 2019

• Siddaganga Institute Of Technology

  Bachelor of Engineering - BE, Computer Science

  2011 — 2015