Ce Gao

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Summary

🤩

Rockstar

Ce Gao is Co-Founder and CEO of TensorChord and a co-chair of the Kubeflow community, bringing 11 years of experience building cloud-native ML infrastructure from China. He leads development of ModelZ (a serverless ML deployment product), envd (reproducible ML dev environments) and pgvecto.rs (a Rust Postgres vector plugin), blending product vision with low-level systems work. Previously he led teams at ByteDance and Tencent Cloud, driving distributed training operators, AutoML and large-scale AI platform delivery after a stint as Tech Lead at Caicloud. An active open-source contributor, he focuses on backend and DevOps across Kubeflow, Cyclone and envd—shipping Python 3 migrations, CI/CD and multi-stage container builds, and integrating tooling like golanglint. Rare among founders, he still commits code to core infra projects, bridging operator-level engineering and commercial ML productization.

11 years of coding experience

Github Skills (37)

dependency-management10

pytorch10

kubernetes10

dockerce10

docker10

buildkite10

python10

configuration-management10

kubeflow10

dockers10

go10

api10

ci-cd10

buildkit10

devops10

Programming languages (27)

CMakefileGoMustacheHTMLJupyter NotebookYAMLJsonnet

Github contributions (5)

tensorchord/envd

Apr 2022 - Jan 2023

🏕️ Reproducible development environment

Role in this project:

Back-end Developer

Contributions:67 releases, 584 reviews, 231 commits in 9 months

Contributions summary:Ce primarily contributed to the development of the MIDI environment, focusing on the core functionalities and features. They set up the project layout, added basic commands, implemented front-end rules, integrated buildkit LLB, and supported its execution. The user's work is evident in the addition of new functions and logic, especially those pertaining to code generation and building.

envdexperiment-trackingai-mlbuildkitdata-science

kubeflow/pytorch-operator

Jul 2018 - Jun 2020

PyTorch on Kubernetes

Role in this project:

Back-end & DevOps Engineer

Contributions:8 reviews, 10 commits, 10 PRs in 1 year 11 months

Contributions summary:Ce primarily focused on updating dependencies and fixing issues within the repository. Their work involved updating vendor files, incorporating specific versions, and addressing comment issues. They also contributed to adding running policies and resource limits for init containers, indicating involvement in infrastructure and configuration. Furthermore, the user integrated golanglint and replaced common with kubeflow/common, suggesting an effort to improve code quality and align with the project's ecosystem.

pytorchkubernetesmachine-learning

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