Joe Liedtke
Software Engineer at Google
Seattle, Washington, United States
Summary
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RockstarJoe Liedtke is a seasoned software engineer with a decade of professional experience and over two decades in software and IT development. Based in Seattle, he currently engineers at Google after a multi-year role as a technical writer, blending strong coding skills with clear documentation and developer experience sensibilities. He contributes to prominent open-source ML tooling—notably Kubeflow—working on pipelines, Argo integration, and docs that help teams build and compose components reliably. Joe’s background includes leadership and delivery roles at Micro Focus and Attachmate, giving him a practical grasp of large-system maintenance and team management. He brings a rare combination of hands-on MLOps engineering and technical writing, making complex cloud-native workflows easier to adopt. Colleagues rely on him for pragmatic refactors that keep integrations with ecosystems like Argo and GCP working at scale.
10 years of coding experience
18 years of employment as a software developer
Stackoverflow
582reputation
24kreached
21answers
1question
Github Skills (26)
markdown10
kubernetes10
python10
kubeflow10
machine-learning10
mlops10
markdown-it10
kubernetes-pods10
argo-workflows10
kubeflow-pipelines10
documentation10
google-cloud-platform9
gcp9
api-design8
data-science7
Programming languages (7)
Github contributions (5)
kubeflow/website
Mar 2019 - Jul 2021
Kubeflow Website
Role in this project:
Technical Writer & Documentation Specialist
Technical Writer & Documentation SpecialistContributions:83 reviews, 26 commits, 44 PRs in 2 years 4 months
Contributions summary:Joe primarily contributed to the Kubeflow website by adding documentation and examples related to building pipelines and components. This includes updating the documentation on Python function-based components, parameter naming, and passing data between components. They replaced existing documentation on building components and pipelines, updating and correcting links to pipeline documentation.
kubeflow
kubeflow/pipelines
Jul 2020 - Mar 2022
Machine Learning Pipelines for Kubeflow
Role in this project:MLOps Engineer
MLOps EngineerContributions:13 reviews, 9 commits, 7 PRs in 1 year 8 months
Contributions summary:Joe primarily focused on integrating and adapting the Kubeflow Pipelines project with the Argo ecosystem. Their work involved updating URLs for Argo components, addressing bugs related to Argo, and refactoring code to align with changes in the Argo workflows. They also contributed to component integration for Google Cloud Platform services. Furthermore, the user made modifications to incorporate features and resolve issues within the API definition.
kubeflowmachine-learningkubeflow-pipelinesmlopskubernetes
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