Kathryn Zhou
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolKathryn Zhou is a software engineer with six years of experience building reliable, production-focused systems and a multidisciplinary background in math, CS, and economics from Harvard and NYU. Currently at Meta, she brings practical MLOps and observability expertise—demonstrated by contributions to the high-profile Ray project where she added Prometheus metrics (disk, network, GPU, cluster stats) and improved dashboard testing. Her career blends hands-on engineering with quantitative finance exposure from private equity roles, giving her a rare lens on data-driven product and infrastructure decisions. Kathryn’s work favors automation, monitoring, and making ML tooling more robust and testable in distributed environments.
5 years of coding experience
Bachelor's degree CS, Bachelor's degree CS at New York University
English, German
Github Skills (14)
collections10
ray10
deploying10
prometheus10
data-collection10
distribute10
python10
metric10
cypress9
dashboard9
dockers7
docker7
machine-learning6
data-science6
Programming languages (2)
Github contributions (5)
ray-project/ray
Feb 2021 - Jun 2021
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:
MLOps Engineer
MLOps EngineerContributions:37 reviews, 10 commits, 11 PRs in 4 months
Contributions summary:Kathryn's primary contributions focus on enhancing the Ray project's infrastructure for monitoring and deployment. They added additional metrics to Prometheus, including disk and network usage, GPU metrics, and cluster statistics. Furthermore, the user implemented a Cypress test for the Ray Dashboard, improving the project's testing capabilities. These changes suggest a focus on observability and automation within the Ray ecosystem.
pythonconsistsruntimetensorflowserving
kathryn-zhou/Cook
Jun 2020 - Jan 2021
Fair job scheduler on Mesos for batch workloads and Spark
Contributions:3 PRs, 198 pushes, 30 branches in 7 months
batchworkloadsbatch-processingscheduleremr
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