At Tecton, we are building an enterprise Feature Store
that is transforming the way companies solve real-world problems with machine learning at scale. Our founding team created Uber's Michelangelo ML Platform
, which has become the blueprint for modern ML platforms in large organizations. We recently received Series B funding
from Sequoia Capital and Andreessen Horowitz, have paying enterprise customers, and have growing teams in SF and NYC. The team has years of experience building and operating business-critical machine learning systems at scale at places like Uber, Google, Facebook, Airbnb, Twitter, and Quora.
A core part of our strategy is to build our feature store technology as open source components through Feast. Feast is increasingly becoming a core part of the modern MLOps stack, with various technology companies adopting it internally as their feature store of choice. Our vision is for Feast to become the industry standard, open source feature store that teams trust in production while providing a seamless path to our managed offering.
We’re hiring a Product Manager to build Feast into the best-in-class open source feature store. In this role, use your experience with data platforms and MLOps to envision and deliver a feature store that is powerful, intuitive, and highly extensible.
You will be involved in all stages of the product life cycle — engaging with customers directly and doing data-driven research, testing hypotheses with fast prototypes, designing features that solve real world problems, collaborating with engineers to ship new tools, and communicating changes internally and externally, to ultimately deliver a world-class product. You will explore complex and exciting technical problems, including API design, data modeling, integrations with machine learning and data quality monitoring frameworks, data versioning, and data discovery.
We are looking for an exceptional Product Manager with a deep understanding of developer workflows, open source communities and a high empathy for both data scientists and ML engineers.