Neetika Singhal

Software Development Engineer 2 at Amazon Web Services (AWS)

San Francisco, California, United States
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Summary

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Neetika Singhal is a Software Development Engineer at AWS with nine years of experience building distributed systems, search, and database features for OpenSearch. With an MS in Computer Science from USC and prior roles at Intuit and PayPal, she blends machine learning and full-stack expertise to deliver production-grade services and data-driven products. Her work spans backend infrastructure, RESTful platforms, event-correlation pipelines, and ML-driven features that have demonstrably improved conversion and operational outcomes. At PayPal she automated an ML ETL and deployment pipeline that reduced alert response time by 30%, and at Intuit she led a SmartLeads project that boosted sales conversions by 40%. Based in San Francisco, she actively contributes to open-source OpenSearch work and maintains a public GitHub showcasing her distributed-systems and search contributions.
code9 years of coding experience
job5 years of employment as a software developer
bookMaster of Science - MS, Computer Science, Master of Science - MS, Computer Science at University of Southern California
bookBachelor of Technology (B.Tech.), Information Technology, Bachelor of Technology (B.Tech.), Information Technology at Indira Gandhi Delhi Technical University For Women
bookAISSCE, AISSCE at Salwan Public School, Gurgaon
bookAISSE, AISSE at Chaman Vatika International School, Ambala
languagesEnglish, Hindi
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Github Skills (18)

search-engine10
nearest-neighbors10
analytics10
java10
restful10
rest10
knn10
opensearch9
opensearch-dashboards9
api-specification9
nearest-neighbor-search8
amazon8
aws6
aws-sdk6
maintenance-mode4

Programming languages (5)

TypeScriptJavaSCSSHTMLPython

Github contributions (5)

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neetikasinghal/OpenSearch

Apr 2023 - Apr 2026

🔎 Open source distributed and RESTful search engine.
Contributions:2 releases, 15 reviews, 267 PRs in 2 years 11 months
restrestfulsearch-engine
neetikasinghal/k-NN

Jan 2025 - Apr 2026

🆕 Find the k-nearest neighbors (k-NN) for your vector data
Contributions:22 pushes, 5 branches in 1 year 2 months
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