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 have previously helped build and scale machine learning platform and infrastructure at Spotify, NVIDIA, and Twitter (pre-X). I have also acted as Engineering Advisor for the non-profit Humane Intelligence, where I worked 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’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.
- “Accelerating Time-to-Production for ML at Hinge”, Ray Summit (2024)
- “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)
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