Caleb Ho
Software Engineer at Meta
Menlo Park, California, United States
Summary
🤩
Rockstar🎓
Top SchoolCaleb Ho is a software engineer in Menlo Park with a decade of experience building developer-facing tools and infrastructure for AI/ML research workflows at Meta FAIR. He blends full‑stack web development (Python, Hack, React, GraphQL) with deep interests in parallel/distributed computation and ML systems to speed experimentation and developer productivity. Caleb has hands-on experience improving open-source research tooling—contributing DevOps and automation enhancements to DeepMind’s OpenSpiel to modernize builds, testing, and packaging. Comfortable across languages and deployment pipelines, he focuses on pragmatic engineering that bridges research and production.
10 years of coding experience
2 years of employment as a software developer
Bachelor of Arts - BA, Mathematics (Honors) and Computer Science, Bachelor of Arts - BA, Mathematics (Honors) and Computer Science at Swarthmore CollegeThe Pingry School
English
Github Skills (12)
pip10
automation10
automations10
python10
cicd10
testing10
cmake9
cpp4
multi-agent3
reinforcement-learning3
coregames3
videogames3
Programming languages (12)
Github contributions (5)
google-deepmind/open_spiel
Oct 2019 - Jan 2020
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
Role in this project:
DevOps Engineer & Automation Engineer
DevOps Engineer & Automation EngineerContributions:7 commits, 1 PR, 8 comments in 2 months
Contributions summary:Caleb focused on improving the build and testing infrastructure of the project. Their contributions include parsing requirements for setup.py, integrating nox for running tests, and creating and modifying Travis CI scripts. They also worked on creating a pip installable package and changing the compiler to clang. This work improved the project's build, testing, and deployment processes.
cppmultiagentgamespythondatamining
calebho/pytorch
Sep 2019 - Jun 2022
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Contributions:3 PRs, 6 pushes, 4 branches in 2 years 9 months
pythongpu-accelerationdeep-learninggpuacceleration
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