A how-to guide for using Kubernetes, Hugging Face, and CoreWeave Kubernetes Service for running an open-source model with the Open WebUI.

Software engineers onboarding to CKS.

Worked closely with PMs, engineers, and other stakeholders to deliver best-in-class onboarding experience.

A highly-praised guide that helps engineers quickly get a sense of CKS's ability to easily run inference on GPUs.

docs.coreweave.com/docs/products/cks/deploy-model

Redesigned and restructured the information architecture for CoreWeave Kubernetes Service documentation to improve user navigation and content discoverability.

Software engineers and DevOps professionals using CoreWeave's managed Kubernetes service.

Analyzed existing content structure and collaborated with product teams to create a logical information hierarchy that makes finding information easier and more efficient for different user journeys.

Improved content organization with clear sections for Clusters, Nodes, Terraform, Authentication, and Reference materials, making it easier for users to find relevant information.

docs.coreweave.com/docs/products/cks

Restructured the information architecture for CoreWeave Observe™ documentation to create a comprehensive observability solution guide.

DevOps engineers and SREs implementing monitoring and observability solutions on CoreWeave infrastructure.

Analyzed user workflows and collaborated with observability experts to organize content around key solutions: Grafana, Metrics, Logs, Telecaster™, and Self-hosted options.

Created a clear information hierarchy that helps users choose the right observability solution for their needs, from managed Grafana to custom self-hosted implementations.

docs.coreweave.com/docs/observability

A technical and mathematical introduction to linear regression and gradient descent, two of the most foundational concepts in machine learning.

Aimed at software engineers new to machine learning.

Collaborated with ML experts and technical writers to help learners grasp at an intuitive level an understanding of linear regression and gradient descent.

A widely taken module by internal and external users worldwide.

developers.google.com/machine-learning/crash-course/linear-regression

A technical introduction to the tasks involved in planning, developing, and maintaining ML and AI models in production.

Aimed at engineers and managers new to machine learning and AI.

Collaborated with ML experts, technical writers, user experience researchers, and animation specialists.

A widely taken course by internal and external users worldwide.

developers.google.com/machine-learning/managing-ml-projects

A gentle introduction to machine learning. The course covers core ML concepts and methodologies.

Aimed at a broad audience with little to no technical background.

Collaborated with ML experts, user experience researchers, and animation specialists.

A widely taken course by internal and external users worldwide.

developers.google.com/machine-learning/intro-to-ml

A technical overview for solving problems with ML.

Aimed at a technical audience who needs a framework for solving problems using machine learning.

Worked with ML experts to understand the key differences and approaches for solving problems with ML.

A widely taken course by internal and external users worldwide.

developers.google.com/machine-learning/problem-framing

Designed and implemented a user-centered homepage to help learners easily find relevant content for their ML educational journey.

Aimed at a primarily technical audience looking for ML-related education.

Worked with UX designers and illustrators to create an appealing homepage that's easily to navigate.

The site has a million plus users a year.

developers.google.com/machine-learning/

Documented a series of Cloud Logging features, like searching and parsing logs from a bespoke query UI, implementing searches using regular expressions, and understanding dashboard metrics.

Aimed at both novice and advanced Cloud Logging users.

Collaborated with engineers, UX designers, and PMs.

Reduced user friction and created mental model to help developers increase productivity.

cloud.google.com/logging/docs/overview

Created a user-centered quickstart guide to help users learn and explore the full functionality of the Debugger.

Aimed at software engineers using Google Cloud.

Worked with the Debugger engineers to understand the key features of the product.

Created a smoother and more intuitive onboarding experience for developers.

Cloud Debugger was deprecated May 2022.

Documented Node.js and Go libraries for OpenTelemetry, an open source telemetry program.

Aimed at software engineers using Google Cloud.

Worked with developer relations engineers to understand the features, common use cases, and workflows developers need to know to use the product.

Helped Google Cloud users understand key implementation and design patterns.

cloud.google.com/trace/docs/overview

Wrote a tasked-based guide for App Engine's PHP runtime environment.

Aimed at software engineers using Google Cloud.

Worked with developer relations engineers to understand the features, common use cases, and workflows PHP developers need to know to use the product.

Helped Google Cloud users understand basic set-up and implementation procedures.

cloud.google.com/appengine/docs