Yuanjie Ding
Software Engineer at Databricks
Germany
Summary
🤩
Rockstar🎓
Top SchoolYuanjie Ding is a software engineer with eight years of experience building high-performance systems, currently at Databricks in Germany. He has a strong background in ML infrastructure and compiler-level optimization from contributions to Microsoft’s nnfusion project, where he implemented kernels, added fp16 support, and integrated freezer tools for TensorFlow and PyTorch. Prior roles at TikTok and a research internship at Microsoft reflect hands-on experience shipping production-grade software and bridging research code to deployable systems. Trained in computer science at Beihang University, he combines low-level performance tuning with practical deployment know-how. Yuanjie’s work shows a pattern of improving build reliability and CUDA integrations—skills that make him effective at optimizing ML workloads end to end. He brings a pragmatic engineering mindset focused on measurable performance gains and maintainable tooling.
8 years of coding experience
3 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Beihang University
Github Skills (9)
cuda10
machine-learning10
c-language10
deep-learning10
cprogramming-language10
cmake9
pytorch8
tensorflow8
roc6
Programming languages (1)
Github contributions (5)
microsoft/nnfusion
Sep 2020 - Mar 2021
A flexible and efficient deep neural network (DNN) compiler that generates high-performance executable from a DNN model description.
Role in this project:
ML Engineer
ML EngineerContributions:2 reviews, 57 commits, 13 PRs in 5 months
Contributions summary:Yuanjie primarily contributed to the development of the neural network compiler, specifically focusing on kernel implementation and performance enhancements. They refactored existing code and added support for fp16, including necessary datatype mappings and integration with CUDA. Furthermore, they were involved in fixing build issues and updating CMake configurations to ensure the project's successful compilation and deployment. They also contributed to the addition and integration of freezer tools for TensorFlow and PyTorch models.
tvmdeep-learningdeep-neural-networkcompilerneural-network
Niupple/BUAA-OS-Niupple
Mar 2019 - Jul 2019
Contributions:138 commits, 34 branches in 4 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.