Pratyush Verma
Founding Engineer at Deductive AI
England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolPratyush Verma is a founding engineer and seasoned software leader with 14 years of experience building resilient, high-performance data infrastructure and distributed systems across startups and tech giants. He led impactful teams at Facebook to modernize Presto/Velox integrations and drove Ads infra optimizations that saved roughly $40M in Opex, and now helps steer a well-funded AI/database startup from 0 to 1. His background spans backend systems at scale—from Flipkart’s billion-image ingestion and mobile platform to Grab’s widely used Go circuit-breaker and an in-house config/logging system—blending deep systems engineering with product-minded execution. An active open-source contributor, he has made substantive backend contributions to the widely used Presto project, improving native execution, memory management, and shuffle/query performance. He also brings entrepreneurial experience (founder of NeuralPainting) and a habit of solving hard operational problems that reduce error rates and cost while enabling large-scale analytics.
14 years of coding experience
11 years of employment as a software developer
B.E. Computer Science, B.E. Computer Science at Birla Institute of Technology, Mesra
Github Skills (14)
javas10
c-language10
cprogramming-language10
presto10
back-end-development10
java10
user-data9
data-set9
data-model9
sql9
spark9
sql-query8
big-data8
hadoop8
Programming languages (5)
Github contributions (5)
prestodb/presto
Dec 2022 - Dec 2022
The official home of the Presto distributed SQL query engine for big data
Role in this project:
Back-end Developer
Back-end DeveloperContributions:155 reviews, 1 commit, 109 PRs in 1 day
Contributions summary:Pratyush primarily contributed to the backend infrastructure of the Presto distributed SQL query engine, focusing on enhancements and fixes within the native execution environment. They implemented access logging for debugging, improved the performance of the exchange source client by passing the correct destination, and addressed issues in memory management and task processing, especially within the native execution and the Spark integration. Their work included refactoring and optimizing code related to shuffle operations and query execution.
distributed-sqlquerybigdataquery-enginesql
vermapratyush/beedoc
Aug 2016 - Apr 2023
Contributions:1 push, 1 branch in 6 years 8 months
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