Joshua Deng
Software Engineer at Meta
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolJoshua Deng is a Software Engineer based in New York with four years of hands-on experience building high-performance systems at Meta after internships across Lyft, Facebook, Proofpoint, and Thomson Reuters. He focuses on backend and ML engineering, contributing to PyTorch's torchrec—helping optimize sharding, sparse feature handling, and embedding table performance in distributed recommendation systems. Comfortable bridging research-grade ML frameworks and production inference, he has practical experience in speech LLM inference workflows at Meta. A UT Austin CS graduate, Joshua pairs a strong foundation in systems and ML with a knack for performance tuning and clear, maintainable documentation in open-source projects.
4 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at The University of Texas at AustinSaratoga High School
Github Skills (8)
pytorch10
recommendation-system10
deep-learning10
python10
gpu9
distributed-systems9
cuda9
machine-learning8
Programming languages (3)
Github contributions (5)
meta-pytorch/torchrec
Nov 2021 - Jan 2023
Pytorch domain library for recommendation systems
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:6 reviews, 98 commits, 160 PRs in 1 year 2 months
Contributions summary:Joshua's contributions center on enhancing the PyTorch domain library for recommendation systems by adding comprehensive docstrings to multiple modules. The primary focus of the user's work appears to be in the optimization of sharding within the framework, specifically related to the management and efficient handling of sparse features and embedding tables in a distributed environment. The commits demonstrate a strong grasp of performance optimization techniques within the PyTorch framework.
pytorchrecommendation-systemgpudeep-learningcuda
joshuadeng/torchrec
Feb 2022 - Sep 2024
Pytorch domain library for recommendation systems
Contributions:324 pushes, 141 branches in 2 years 6 months
pytorchrecommendation-systemsdomainrecommendation
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