• Contributed to LinkedIn’s ID Verification initiatives, enhancing platform security with verification methods such as work email, government-issued IDs, and Microsoft Azure Active Directory. Designed scalable APIs, flexible backend models, and integrated external services like Microsoft SDKs and Clear API. Utilized Samza for stream processing and Kafka with database change logs, combined with a name-matching algorithm, to ensure accurate verification updates. Strategically placed ID verification invitations in LinkedIn’s news feed, in-app notifications, and targeted emails, driving 100 million verifications in 7 months.

• Built a DMA (Digital Markets Act) read-only service from scratch to handle over 4 million QPS with

sub-5ms latency, operating in parallel with the existing settings service to ensure full DMA compliance.

Achieved a 50% latency reduction compared to the existing service by prefetching data into cache using

offline jobs, implementing in-memory metadata mapping, fine-tuning memory usage, and optimizing core allocation for maximum resource utilization, successfully passing stress tests.

• Built demographic service to support Self ID forms, ensuring secure handling of PII and full compliance

with CCPA, GDPR, and HIPAA. Automated audit scripts for continuous data security monitoring and

developed efficient ETL Spark jobs for offline table generation. Collaborated with data scientists to ensure data integrity, tracking, and optimized search indexing. These efforts improved the user experience of self-identification forms, increasing Self-ID adoption by 31%, from 5.5 million to 11.5 million in six months.

• Developed a Python tool to automate onboarding of new settings from partner teams, reducing manual

effort by 80% in backend work. The tool automates metadata insertion into a relational database, generates auto-merged GitHub PRs for document schema updates, and deploys changes to the testing environment, streamlining the process.

• Reduce 21% p95 latency of the credit and refund real-time service by adding cache (Redis), fine-tune the performance of ETL (extract, transform and load) jobs, optimize feature extraction runtime of machine learning models, and refractor the rule runner from risk engines.

• Create service health metrics, build various alerting systems and dashboards using Wavefront, Chrono-

sphere, Chartio, and Splunk to proactively monitor the risk service.

• Identify new fraud vectors and block dynamically evolving fraud patterns timely. Create high-precision

rule-based solutions hybridized with machine learning models to enhance the friction to suspicious users (Kotlin/Python).

• Lead the fraud precision enhancement projects which reduce false-positive and the agent MTO (manual take over) cost, increase retention rate by extracting data from case studies, and build the business analytic monitoring system to track fraud trending.

Developed user interface of high-quality streaming service application with restricted memory and limited bundle size among multiple platforms, such as Roku streaming stick, PlayStation, Xbox and other living room devices.

• Improved hierarchy of frontend caches and reduced turnaround time of remote procedure call for content query while loading applications.

• Implemented two-step verification interface for login authentication, sign up flow, and account information page with minimized API calls.

• Prototyped multiple minimum viable products such as navigation bar, movie content search filter interfaces and integrated analytical data tracking for A/B testing.

• Developed parental control with pin-code enabled feature and specific frame-blocking with interaction

dialog boxes to bring kid-friendly watching environment.

• Improved the numerical accuracy and optimized the runtime of linear solvers with fine tuned parameters of lithography simulation models on distributed systems.

• Developed C++ recipe to verify model-apply algorithms. Maintained and debugged call-stacks, memory and runtime using GDB, Valgrind, and Callgrind for computational lithography software.

• Designed model-apply evaluation tools of computational lithography software for image contour extraction, scalability, performance and accuracy with statistical analysis and data visualization on distributed systems.

• Architected test bank frameworks for unit test using MySQL and Python with continuous integration and code version control system using Jenkins and Perforce.

• Directed software release deliveries, managed source code change-lists with impact assessment, adopted agile program for cross-team cooperation, and conducted new-hire training and mentoring program.