stripe > stripe Employee Directory > Bowen Deng
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Bowen Deng
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Bowen Deng's Current Workplace
StripeCompany Size
2500+
Amount Raised
$8.7B
Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Headquartered in San Francisco and Dublin, the company aims to increase the GDP of the internet.
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Notable Investors
Google, Andreessen Horowitz, Sequoia Capital, Y Combinator, General Catalyst
FinTech
Finance
Enterprise
Mobile Payments
IT Infrastructure
Financial Services
E-Commerce Platforms
Cloud Infrastructure
Experience
Software Engineer
Stripe · Full-time
Feb 2022 - Present
• 3 yrs 6 mosSoftware Engineer
Snap Inc. · Full-time
Feb 2021 - Feb 2022
• 1 yr 1 mo• Design, implement and operate the internal infrastructure for machine learning.
Intelligent Retail Lab
Feb 2018 - Feb 2021
Senior Software Engineer
Oct 2019 - Feb 2021
• 1 yr 5 mos• Led the architecture and implementation of an in-house machine learning platform that streamlined the entire end-to-end process, including data ingestion and pre-processing, model training and optimization, performance evaluation, and continuous model deployment.
• Developed and implemented image similarity models for retail items using semi-supervised learning techniques to overcome noisy labels, resulting in a 12% improvement in F1 score compared to competitor's classification approach.
• Optimized input pipelines for large datasets by leveraging Bigtable, achieving a 2x speedup for model training.
Software Engineer
Feb 2018 - Oct 2019
• 1 yr 9 mos• Designed and implemented rstream, a stream processing library that supports automatic state persistence and failure recovery with reference counting
• Enhanced in-house tracing infrastructure around gRPC and Kafka, making profiling and debugging more accessible across services
• Developed event-sourced microservices for data ingestion and aggregation
• Developed and maintained CI/CD pipelines on Azure DevOps for production services
• Implemented libraries and development tools to support remote debugging for production services (written in Node.js or Python) on Kubernetes, and significantly shorten troubleshooting time for several production issues
Software Engineer Intern
Facebook · Internship
May 2017 - Aug 2017
• 4 mos• Built a system detecting landing page cloaking (showing reviewers benign pages, but redirecting users to other malicious pages), and the system enforced 130K+ Ads within the first week of its release with a 0.04% false positives rate
• Developed a time-windowed counter service processing 12K log events sampled from mobile clients in real-time and aggregated the events to high-level features for cloaking detection
Research Intern
Microsoft · Internship
Apr 2015 - Feb 2016
• 11 mos• Developed Cosmos pipelines analyzing large scale (TB-level) semi-structured transactional logs from Microsoft Azure and Office 365, and helped the product teams caught several system failures in their early stage
• Analyzed performance characteristics of distributed jobs for log analysis, identified performance bottlenecks caused by poor data locality and redundant computation, and performed optimization archiving 10x speedup
• Designed an extendable log analysis framework and integrated several existing log-analysis algorithms into the framework
Software Engineer
Stripe · Full-time
Feb 2022 - Present
• 3 yrs 6 mosSoftware Engineer
Snap Inc. · Full-time
Feb 2021 - Feb 2022
• 1 yr 1 mo• Design, implement and operate the internal infrastructure for machine learning.
Intelligent Retail Lab
Feb 2018 - Feb 2021
Senior Software Engineer
Oct 2019 - Feb 2021
• 1 yr 5 mos• Led the architecture and implementation of an in-house machine learning platform that streamlined the entire end-to-end process, including data ingestion and pre-processing, model training and optimization, performance evaluation, and continuous model deployment.
• Developed and implemented image similarity models for retail items using semi-supervised learning techniques to overcome noisy labels, resulting in a 12% improvement in F1 score compared to competitor's classification approach.
• Optimized input pipelines for large datasets by leveraging Bigtable, achieving a 2x speedup for model training.
Software Engineer
Feb 2018 - Oct 2019
• 1 yr 9 mos• Designed and implemented rstream, a stream processing library that supports automatic state persistence and failure recovery with reference counting
• Enhanced in-house tracing infrastructure around gRPC and Kafka, making profiling and debugging more accessible across services
• Developed event-sourced microservices for data ingestion and aggregation
• Developed and maintained CI/CD pipelines on Azure DevOps for production services
• Implemented libraries and development tools to support remote debugging for production services (written in Node.js or Python) on Kubernetes, and significantly shorten troubleshooting time for several production issues
Software Engineer Intern
Facebook · Internship
May 2017 - Aug 2017
• 4 mos• Built a system detecting landing page cloaking (showing reviewers benign pages, but redirecting users to other malicious pages), and the system enforced 130K+ Ads within the first week of its release with a 0.04% false positives rate
• Developed a time-windowed counter service processing 12K log events sampled from mobile clients in real-time and aggregated the events to high-level features for cloaking detection
Research Intern
Microsoft · Internship
Apr 2015 - Feb 2016
• 11 mos• Developed Cosmos pipelines analyzing large scale (TB-level) semi-structured transactional logs from Microsoft Azure and Office 365, and helped the product teams caught several system failures in their early stage
• Analyzed performance characteristics of distributed jobs for log analysis, identified performance bottlenecks caused by poor data locality and redundant computation, and performed optimization archiving 10x speedup
• Designed an extendable log analysis framework and integrated several existing log-analysis algorithms into the framework
Education
- 2016 - 2017Carnegie Mellon UniversityMaster’s Degree
- 2013 - 2015Shanghai Jiao Tong UniversityPh.D. (Dropped out), Computer Science and Engineering
- 2016 - 2017Carnegie Mellon UniversityMaster’s Degree
- 2013 - 2015Shanghai Jiao Tong UniversityPh.D. (Dropped out), Computer Science and Engineering
- 2009 - 2013Wuhan UniversityBachelor’s Degree, Software Engineering