Tung Vu is a highly analytical Software Engineer and MSc candidate specializing in high-performance distributed systems. He excels at building and optimizing scalable infrastructure, demonstrated by his role engineering the core C++ ML serving pipeline at Google LLC. He consistently delivers measurable results, having achieved a 30% reduction in critical API response time through meticulous system profiling and refactoring. His expertise spans C++, Python, Linux environments, and distributed concurrency.

Tung (Tom) Vu

Tung Vu is a highly analytical Software Engineer and MSc candidate specializing in high-performance distributed systems. He excels at building and optimizing scalable infrastructure, demonstrated by his role engineering the core C++ ML serving pipeline at Google LLC. He consistently delivers measurable results, having achieved a 30% reduction in critical API response time through meticulous system profiling and refactoring. His expertise spans C++, Python, Linux environments, and distributed concurrency.

Available to hire

Tung Vu is a highly analytical Software Engineer and MSc candidate specializing in high-performance distributed systems. He excels at building and optimizing scalable infrastructure, demonstrated by his role engineering the core C++ ML serving pipeline at Google LLC. He consistently delivers measurable results, having achieved a 30% reduction in critical API response time through meticulous system profiling and refactoring. His expertise spans C++, Python, Linux environments, and distributed concurrency.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
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Language

Javanese
Advanced
Aragonese
Advanced

Work Experience

Software Engineering Intern at Google LLC
August 31, 2024 - October 16, 2025
Designed and implemented a machine learning pipeline for bidding recommendations in Google Search Ads 360, using Python, C++, Go, and Protocol Buffers; deployed ML model in production; collaborated with cross-functional teams; leveraged CI/CD pipelines and Git for version control; analyzed large-scale conversion-rate statistics with SQL to evaluate model performance.
Software Engineer (Co-op) at 3Pillar Global
April 1, 2024 - October 16, 2025
Executed API testing strategies using ZAP to elevate security standards across a Spring Boot project. Implemented a data processing pipeline with Java and Spring Boot, reducing API response time by 30%. Developed a modal component in React for a polished and responsive user interface.
Graduate Research Assistant at Concordia University
May 1, 2022 - Present
Currently researching asynchronous distributed shortest paths algorithms for large-scale 5G message routing. Wrote a Java library implementing Elkin's synchronous sub-linear time distributed shortest paths in the CONGEST model. Authored a thesis on Distributed single-source shortest paths (SSSP) performance of Bellman-Ford and Elkin algorithms in the CONGEST model.
Machine Learning Engineering Intern at FPT Software AI Center
September 1, 2023 - October 16, 2025
Modeled performance of CUTLASS written in CUDA and C++ for high-performance matrix multiplication. Profiled CUDA applications using Nsight Systems and Nsight Compute to analyze computational performance. Built a Python/C++ pipeline to generate a large set of optimized / non-optimized OpenCL kernels for performance modeling.
Software Developer at Niteco Vietnam
June 1, 2020 - October 16, 2025
Designed a database in an employee management system to ensure database consistency using SQL Server. Investigated and fixed authentication and authorization issues in .NET Core and Node.js to secure access for a large user base. Implemented cronjobs to periodically send notification emails using C#, Amazon Simple Email Service (SES), and Jenkins.
Software Engineer at NashTech Ltd.
September 1, 2019 - October 16, 2025
Implemented and integrated a new location service into an existing system to ensure location database consistency using .NET Core, RabbitMQ, Hangfire, Apache Lucene.NET, and SQL Server. Developed features in a studio management system using .NET Core, AWS Lambda, Amazon SQS, Elasticsearch, and CQRS, improving user engagement. Implemented BFS to solve a directory tree pagination problem, reducing client download/upload time by 30%.

Education

Master of Science in Computer Science at Concordia University
May 1, 2022 - June 1, 2025
Bachelor’s Degree in Software Engineering at FPT University
August 1, 2020 - January 1, 2022

Qualifications

Concordia University Merit Scholarship
January 1, 2022 - December 31, 2023
Mitacs Research Bursary
January 1, 2022 - December 31, 2024

Industry Experience

Software & Internet, Computers & Electronics, Professional Services, Media & Entertainment

Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
See more