Working on LLMs.

Previously, I was a software engineer working on open-source Kubernetes at Google, building and maintaining Kubernetes developer tools such as minikube and skaffold. I also worked on machine learning pipelines as a maintainer of the Kubeflow project. Before Google, I worked at The Blackstone Group in NYC.

I received a BA in Mathematics from Columbia University. I have an MBA from Stanford Graduate School of Business, where I was an Arjay Miller Scholar.

• Twitter (@mattrickard)
• LinkedIn (msrickard)
• GitHub (r2d4)
• Threads (matt.rickard)
• Email ([email protected])

Software

AI

• ReLLM - Constraining LLMs pre-generation logits via regex.
• ParserLLM - Context-free grammar constraints for any LLMs.
• Kubeflow - Machine Learning Toolkit for Kubernetes
• @react-llm - Browser-based LLM inference. See chat.matt-rickard.com.
• LLaMaTab - Chrome-extension LLM inference.
• openlm - OpenAI-compatible Python library that can call any LLM.
• llm.ts - OpenAI-compatible TypeScript library (browser, node, deno)
• ScapeNet and osrs-ocr - Vision and text model for an MMORPG

Distributed Systems

• minikube: run Kubernetes locally
• skaffold: Kubernetes developer tool
• dacc: Cache-efficient, sandboxed, builds as code
• virgo: graph-based configuration language
• distroless: language runtime docker images without an operating system
• mockerfile: alternative dockerfile frontend
• docker-merge: merge docker images
• minikube-kvm-driver: manage virtual machine lifecycles with KVM
• Kubeflow - Machine Learning Toolkit for Kubernetes