Jingjie Ni
Software Engineer at Google
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolJingjie Ni is a software engineer in the San Francisco Bay Area with four years of industry experience focused on ads infrastructure, machine learning, geospatial analysis, distributed systems, and databases. At Google, he builds ML-driven real-time user modeling and audience targeting for YouTube and other Google properties, while earlier work at HP/Vertica delivered in-database geospatial indexing and machine learning capabilities for big data analytics. He excels at designing scalable, high-performance systems that bridge research-grade modeling with production constraints and latency-sensitive serving. Jingjie is researching next-generation modeling paradigms and building scalable foundation model systems, signaling a move from traditional ML pipelines toward large-model infrastructure. Colleagues describe him as someone who enjoys tackling hard algorithmic problems and collaborating with strong engineering teams. His combined background in in-db analytics and real-time ad systems gives him a unique perspective on operationalizing advanced models at scale.
5 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 Xi'an Jiaotong UniversityMaster of Science, Computer Science, Master of Science, Computer Science at Tufts University
Chinese, English
Github Skills (42)
evaluation9
artificial-intelligence9
benchmark9
python9
large-language-models9
extraction9
dynamic-data9
ctp9
transformer-models9
foundation-models9
evaluation-framework8
sequence-to-sequence8
command-line-tool8
data-extraction8
pytorch8
Programming languages (3)
Github contributions (5)
JinjieNi/JinjieNi.github.io
Dec 2021 - Mar 2026
Contributions:420 pushes, 1 branch in 4 years 3 months
JinjieNi/EasyLiterature
Oct 2023 - Aug 2024
EasyLiterature is an open-sourced, Python-based command line tool for automatic literature management.
Contributions:4 releases, 3 PRs, 60 pushes in 10 months
command-line-toolpython
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