# Srihari Shankar

> Software Engineer At Amazon Advertising

Location: New York City Metropolitan Area, United States
Profile: https://flows.cv/srihari

## Work Experience
### Software Development Engineer II @ Amazon
Jan 2021 – Present
Building a highly scalable ad serving infrastructure
- Designed and implement ML data pipeline using ECS, S3 and Dynamo DB to optimize performance for ad programs such as prime video and audio ads.
- Design and develop multibid feature for the Ad pacing engine which increased impressions volume by 5%.
- Design and develop a high volume caching service using Redis, Kinesis, Kafka and ECS to vend complex time series data to simplify monolithic pacing service.
- Developed and launched a new feature called ”Simplified Pacing Profile” which streamlined Amazon’s pacing profile options, resulting in a 1% increase in revenue.
- Develop experimentation feature that allowed ML engineers to design and test models for understanding and targeting anonymous traffic, in response to iOS privacy changes, resulting in improved conversion rate of ad campaigns.
- Mentor and develop new engineers on the team.

### Software Development Engineer I @ Amazon
Jan 2019 – Jan 2021 | New York, United States
- Designed and Developed a service using Elasticsearch and AWS Services such as SQS, S3 etc to ingest 1M emails a month to improve manual invoice reconciliation time from a week to 1 day.
- Developed an improved automated invoice reconciliation system that had a 30% improvement over the legacy system using AWS Neptune, SQS, S3 and Elasticsearch.
-  Productionized a Sum of Subsets algorithm, by using Dynamic programming and a K-SUM algorithm that improved invoice matching by 25%.
- Migrate from Kakfa to Redis to reduce on-call load by 20 percent.
- Migrated Firetablet Ad Serving from old legacy system to a newer more reactive system that is projected to increase revenue by 66M dollars.

### Software Engineering Intern @ AI.Reverie
Jan 2019 – Jan 2019 | Greater New York City Area
- Wrote scripts to convert multiple annotation formats to MSCOCO that scaled to hundreds and thousands of images using Python and Docker.
-  Built WebApp in Flask, Postgres, React and Docker to query metadata of up to 100,000 images which could scale to millions of images
- Worked on Android App that ran on security camera to run various Computer Vision models such as falling detection and object detection.

### hackNY Fellow @ hackNY.org
Jan 2019 – Jan 2019 | Greater New York City Area
Interned at AI Reverie and worked on a social good project.

### Software Engineering Intern @ Amazon
Jan 2018 – Jan 2018 | Seattle, Washington, United States
- Built distributed Job in Java to move 10 million records on a weekly basis to Elasticsearch using Bulk API from Oracle Database.
- Created service using Java to power a dashboard built in React/Typescript for financial analysts to streamline reconciliation of receipts to invoices.
- Built search engine in Java and Elasticsearch to quickly and efficiently search customer information.

### Student Researcher @ InfoSeeking
Jan 2017 – Jan 2018

### Software Engineering in Test Intern @ iconectiv
Jan 2017 – Jan 2017
-Built a JSON validation tool in Python that will be in used in multiple products.
-Developed an easy to use multithreaded test framework in Selenium to help testers easily create GUI tests that could execute 126 tests in 5 min.
-Worked with DevOps team to dockerize the test framework.
-Prototyped automation as a service using spark-java for future use.

### Research Assistant @ Aresty Research Center for Undergraduates at Rutgers University
Jan 2016 – Jan 2017 | New Jersey
-Set up server infrastructure for developing experiments.
-Developing AI assistant for Minecraft to collect data on collaboration and improve player experience.
 -Implemented machine learning algorithms to collect data and perform actions to improve player collaboration.
 -Leading team of other research assistants to create a Minecraft mod by providing mentoring.

### Software Engineering Intern @ Nibbly: Eat & Play
Jan 2016 – Jan 2016
-Ported server from an old Parse instance to AWS Lambda.
-Set up Firebase database for analyzing user swipes and behavior. 
-Redesigned backend of iOS by optimizing the core algorithm behind the app.
-Improved speed of app by 57%.


## Education
### Bachelor of Science (BS) in Computer Science
Rutgers University
Jan 2015 – Jan 2019


## Contact & Social
- LinkedIn: https://linkedin.com/in/srihari-shankar-a45029134
- GitHub: https://github.com/Sail338
- GitHub: https://github.com/Sail338

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Source: https://flows.cv/srihari
JSON Resume: https://flows.cv/srihari/resume.json
Last updated: 2026-03-23