Sheng-chi Liu
Imaging Algorithm Engineer at Google
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolSheng-chi Liu is an Imaging Algorithm Engineer at Google with seven years' experience building machine-learning and cloud-native systems, combining a Cambridge PhD with hands-on production engineering. Previously an ML Engineer and AI Resident at X (the moonshot factory), he blends research rigor with pragmatic implementation across imaging and distributed compute. He is an active open-source contributor and maintainer-level collaborator on major projects like Ray and Apache Submarine, contributing runtime packaging, controller logic, and DevOps automation that help run ML workloads at scale. Based in Mountain View, he bridges backend, DevOps, and algorithm development, often surfacing subtle infrastructure fixes (e.g., owner references and event handlers for CRDs) that improve platform reliability.
7 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, ENGINEERING, Doctor of Philosophy - PhD, ENGINEERING at University of Cambridge
Github Skills (18)
kubernetes10
controller10
python10
led-controller10
controls10
go10
kubernetes-pods10
ray10
controller-advice10
documentation10
dockers9
docker9
packaging9
github8
yaml8
Programming languages (10)
Github contributions (5)
apache/submarine
Mar 2021 - Apr 2022
Submarine is Cloud Native Machine Learning Platform.
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:22 reviews, 35 commits, 32 PRs in 1 year 1 month
Contributions summary:Sheng-chi's contributions primarily focus on developing features for the Submarine cloud-native machine-learning platform. They modified the controller code to read the Submarine CRD spec. In addition, they implemented the ability to create submarine-database resources. Furthermore, they added the ability to set owner references on resources. Finally, the user worked on setting up event handlers for various resources.
machine-learning-platformlearning-platformdeep-learningnotebookdocker
ray-project/ray
Apr 2024 - Apr 2025
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Role in this project:Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:229 reviews, 121 PRs, 369 comments in 11 months
Contributions summary:Sheng-chi primarily contributed to documentation improvements and code refactoring. They fixed documentation issues, such as code block rendering and replacing file paths. Additionally, the user implemented a single-file module for runtime environments, which involved changes in packaging. They also addressed code style issues by replacing flake8 and isort with ruff and replacing Redis function arguments.
pythonconsistsruntimetensorflowserving
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