Jingyi Zhu
Senior Software Engineer at Microsoft
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolJingyi Zhu is a Senior Software Engineer based in the San Francisco Bay Area with five years of experience building cloud and ML-enabled systems at Microsoft. She has progressed through multiple engineering roles in Azure Machine Learning and now contributes to production-grade tooling for LLM applications, including meaningful commits to Microsoft’s popular PromptFlow project where she improved RAG pipeline support and added new embedding model integrations. Jingyi combines backend engineering, build-system work, and ML-indexing expertise to streamline retrieval-augmented generation workflows and serverless connection handling. Her background includes hands-on internships automating big-data workflows at Kaiser Permanente and a CS degree from UC Davis, reflecting a practical focus on data-heavy, production systems. Colleagues describe her as a pragmatic problem-solver who bridges research-facing ML components and developer-centric deployment plumbing.
4 years of coding experience
4 years of employment as a software developer
Bachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at University of California, Davis
Github Skills (9)
prompt-engineering10
azure-machine-learning10
python10
ai10
prompter10
api-ai10
prompt10
llm9
co8
Programming languages (4)
Github contributions (5)
microsoft/promptflow
Apr 2024 - Sep 2024
Build high-quality LLM apps - from prototyping, testing to production deployment and monitoring.
Role in this project:
ML Engineer
ML EngineerContributions:17 reviews, 19 PRs, 56 pushes in 5 months
Contributions summary:Jingyi's commits primarily focus on enhancing the `promptflow-rag` component within the `microsoft/promptflow` repository. They introduce support for new embedding models, including Cohere, and refine serverless connection handling for improved flexibility. Furthermore, they modify the build process to accommodate AzureAISearchSource as an input. These changes streamline the creation and management of MLIndex, which is central to the repository's RAG (Retrieval-Augmented Generation) capabilities, as seen in their direct modifications to the build_index function.
aiai-application-developmentai-applicationschatgptgpt
jingyizhu99/azure-sdk-for-python
Nov 2023 - May 2024
This repository is for active development of the Azure SDK for Python. For consumers of the SDK we recommend visiting our public developer docs at https://docs.microsoft.com/python/azure/ or our versioned developer docs at https://azure.github.io/azure-sdk-for-python.
Contributions:132 pushes, 13 branches in 6 months
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