Sasha Sheng
Co-Founder at TypeSafe AI
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolSasha Sheng is a seasoned software and product engineer with 11+ years of experience who now co-founds TypeSafe AI after leading research and engineering efforts at Facebook across iOS, backend data labeling, multimodal AI and generative models. She has bridged research and product by contributing to FAIR’s open-source multimodal framework (MMF), publishing on VQA and text-to-video work, and shipping full-stack AI demos using cutting-edge diffusion methods. A builder of communities, she founded the DeepLearners study group and led company-wide initiatives on human annotation excellence, combining technical depth with strong people leadership. Based in the San Francisco Bay Area, Sasha pairs hands-on engineering (OSS contributions and feature work on prominent repos) with startup strategy and teaching—she also teaches creative coding and creates social content focused on awareness and creativity. An oft-overlooked thread in her profile is a long-standing interest in early childhood development, parenting and mental health, which informs her human-centered approach to AI and product design.
11 years of coding experience
10 years of employment as a software developer
Stanford Ignite Certificate Program in Innovation and Entrepreneurship Business, Stanford Ignite Certificate Program in Innovation and Entrepreneurship Business at Stanford University Graduate School of BusinessB.S.E Computer Science Engineering, B.S.E Computer Science Engineering at University of MichiganBachelor's degree, Bachelor's degree at University of Michigan College of EngineeringB.S.E Mechanical Engineering, B.S.E Mechanical Engineering at Shanghai Jiao Tong University
English, French, Chinese
Github Skills (19)
pytorch10
python10
pytest9
deep-learning8
pytorch-lightning8
machine-learning8
pre-trained-model7
black-formatter7
formatting7
formatter7
multimodal7
trainings7
modeling7
code-formatting7
data-handling6
Programming languages (8)
Github contributions (5)
facebookresearch/mmf
Aug 2020 - Sep 2021
A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:42 reviews, 69 commits, 101 PRs in 1 year 1 month
Contributions summary:Sasha primarily contributed to fixing and improving the codebase, addressing reformatting errors and running code linters. They implemented features, such as adding support for epoch-based training, and adding split dataset functionality. Their work also involved refactoring and updating dependencies. The user also added a feature to allow passing in model's file path for from_pretrained.
pytorchmodular-frameworkdialogvisionvision-language
abrar-khan007/mmf
Jan 2021 - Jul 2021
A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
Contributions:145 commits in 6 months
modular-frameworkvisionvision-languagedeep-learningcomputer-vision
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