Deepak Mahudeswaran
Staff Software Engineer at Clari
Sunnyvale, California, United States
Summary
👤
Senior🎓
Top SchoolDeepak Mahudeswaran is a Staff Software Engineer based in Sunnyvale with a decade of experience building scalable backend systems and data pipelines. He blends research-grade ML/NLP expertise—earned during graduate work on fake news detection and published datasets—with practical engineering delivered across roles at Clari and earlier at Micro Focus and Amazon. Deepak has contributed to notable open-source projects like Netflix/conductor and built data collection infrastructure for the widely used FakeNewsNet dataset, showing strength in both distributed systems and data engineering. He’s adept at performance tuning and system refactors, having improved throughput and reliability through targeted data model and Redis client fixes. Colleagues rely on him to bridge research insights and production realities, turning experimental models into robust, maintainable services. Quietly curious, he often surfaces non-obvious gains by rethinking data collection and indexing strategies to scale analytics workloads.
10 years of coding experience
8 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at Arizona State UniversityBachelor’s Degree Computer Science, Bachelor’s Degree Computer Science at Anna University Chennai
English, Tamil
Stackoverflow
223reputation
13kreached
10answers
8questions
Github Skills (38)
apim10
python10
redis10
data-engineering10
amazon-elasticsearch10
distributed-systems10
workflow-engine10
webscraping10
java10
javas10
elasticsearchquery10
api10
aws-elasticsearch10
spring-boot10
elasticsearch10
Programming languages (3)
Github contributions (5)
KaiDMML/FakeNewsNet
Sep 2018 - Dec 2019
This is a dataset for fake news detection research
Role in this project:
Data Engineer & Backend Developer
Data Engineer & Backend DeveloperContributions:29 commits, 2 PRs, 13 pushes in 1 year 3 months
Contributions summary:Deepak primarily focused on developing the data collection infrastructure for the fake news detection dataset. Their contributions include creating components for collecting user profiles, tweets, and news articles. They also integrated with Twitter APIs using the Twython library and utilized web archiving to retrieve missing news articles. The user refactored data collection modules for better organization and efficiency, and adjusted CSV parsing for larger data sets.
newsdatasetfake-news-detectionfake-news
Netflix/conductor
Jan 2020 - Jun 2021
Conductor is a microservices orchestration engine.
Role in this project:Backend Developer
Backend DeveloperContributions:1 review, 24 commits, 21 PRs in 1 year 5 months
Contributions summary:Deepak contributed to the core functionality of the Conductor engine by implementing and modifying backend services. Their work involved making task execution logging optional and enhancing the configuration related to it. They also addressed a Redis cluster client issue, refactoring and adding tests to improve reliability. Furthermore, the user enabled optional event message indexing and indexing related configurations, which suggests a focus on improving data indexing within the Conductor system.
spring-bootconductororchestrationworkflow-enginegrpc
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