# Guowei Jiang

> 2 YOE SDE & ML System Engineer @TikTok AI-Lab| ML System Intern @ByteDance AML-Foundation ML System| MSIN @CMU |SDE Intern @Alibaba Cloud |CS Alum @HUST

Location: San Francisco Bay Area, United States
Profile: https://flows.cv/guowei

Experienced Software Development Engineer implemented 20,000+ QPS Generative AI projects at TikTok.
Adept at optimizing GPU service performance and designing ML frameworks and served 150+ services.
Skilled in microservices architecture, Kubernetes, and GPU Inference acceleration. Mostly using Python and C++.
Back to school for Master at CMU in 2023. Now seeking new opportunities in Late 2024.

## Work Experience
### Software Development Engineer II @ TikTok
Jan 2021 – Present
Design scalable AI models and Kubernetes-based GPU service frameworks, optimize hardware performance and legacy services, and implement a microservices architecture with high availability and efficiency from 2021 to 2023 in TikTok AI-Lab

- Project: AI-Manga : [BEST effect throughout TikTok's history as of today!!! - Highlighted by Zhu Wenjia, Global TikTok R&D Chief, during the CEO Business Talk at the 11th ByteDance Anniversary in March 2023]. 

  - Led the initial engineering design and service framework support for the model, ensuring stability and handling high traffic (peak QPS 20,000+) on the Big Day. Decided immediate downgrade solutions for online service issues and then coordinated cross-department troubleshooting
  - Customized optimizations for fixed hardware using TensorRT and improved the generation algorithm performance by 1.6x on selected GPU.

  - Tiktok Online Service: https://www.tiktok.com/sticker/AI-Manga-6048208   
  - Technial Share: https://cloud.tencent.com/developer/article/2228816


- Platform Infrastructure: Designed and implemented Kubernetes GPU service framework, Ivory.
  - Provides resource management (e.g. GPU scheduling, monitoring, resource isolation) by injecting underlying CUDA C++ library.
  - Integrates upper logic including RPC, HTTP, RocketMQ and Kafka interface exposure, compliance audit and internal K6 grafana to orchestrate the whole service lifecycle.


- Legacy Service Optimization: Developed a pipe based C++ - Python library to cross the GIL while maintaining thread safety to improve inference phase efficiency. Optimized a critical legacy service based on the library (20 to 45 QPS/T4), saved 150+ GPU instances and received a spot bonus.

- Microservices Architecture: Take the lead in the migration of a monolithic service into 3 parts of microservices and implemented CI/CD pipelines based on Internal Jenkins and GitLab. The system achieved 99.99% Availability SLA while handling 3,000+ QPS after deployment over 6 months.

### Machine Learning System Intern @ ByteDance
Jan 2024 – Present | Seattle, Washington, United States
Participate in the development of a comprehensive Model Resource Traking Platform - Lineage to manage AI asset collected from HDFS, Data Lake with Apache Iceberg, and Model Zoo.

### Software Engineer Internship @ Alibaba Group
Jan 2020 – Jan 2020
- Developed a graph-based frequent itemset analysis algorithm for CI/CD pipeline data, stored in GraphDB, processed with GraphQL, achieving 75.5% accuracy over two months.
- Utilize Helm for managing Kubernetes applications through Helm charts for templating and versioning.
- Participated in Prometheus monitoring module update for the Alibaba Hybrid Cloud Parent Image.


## Education
### Master's degree in Computer Systems Networking and Telecommunications
Carnegie Mellon University

### Bachelor's degree in Computer Science
Huazhong University of Science and Technology


## Contact & Social
- LinkedIn: https://linkedin.com/in/guoweij

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Source: https://flows.cv/guowei
JSON Resume: https://flows.cv/guowei/resume.json
Last updated: 2026-03-29