Jonathan Jin
Machine Learning Software Engineer

I’m a machine learning engineer with a specialization in platform and infrastructure. I am currently a Staff ML Engineer at Hinge building out the company’s ML platform and infrastructure. I am also the Engineering Advisor for the non-profit Humane Intelligence, where I work with Dr. Rumman Chowdhury to build a community of practice around the burgeoning field of algorithmic audit and evaluation in service of responsible AI.

I have previously helped build and scale machine learning platform and infrastructure at Spotify, NVIDIA, and Twitter (pre-X).

I’ve also worked on site reliability and observability infrastructure at Uber, contributing to the systems that ultimately led to the creation of M3DB and Chronosphere.

I’m a mildly traumatized proud alumnus of the University of Chicago, where I studied computer science and economics.

• cnvrg.io: “AI Developers to Watch 2023”

• “How Spotify is Navigating an Evolving ML Landscape with Hendrix Platform”, TWIMLcon (2022)
• “Empowering Traceable and Auditable ML in Production at Spotify with Hendrix”, MLconf San Francisco (2022)
• “Scaling Kubeflow for Multi-tenancy at Spotify”, KubeCon + CloudNativeCon North America (2021)
• “ML Workflows at Twitter: Lessons Learned”, AI NEXTCon New York (2019)

• Hugging Face Open-Source AI Cookbook: “Building a RAG Ebook ‘Librarian’ Using LlamaIndex”

• Linkedin
• GitHub
• Hugging Face

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