At Tecton, we are on a mission to bring world-class Machine Learning to every product and customer experience. Tecton’s founders developed the first Feature Store when they created
Uber’s Michelangelo ML platform. In pursuit of bringing ML to every production application, we have since brought the leading commercial feature store to market and built the most popular open-source feature store.
We are funded by Sequoia Capital and Andreessen Horowitz and have a fast-growing team that works out of SF, NYC, and remotely. Our team has years of experience building and operating business-critical machine learning systems at leading tech companies like Uber, Google, Facebook, Airbnb, Twitter, and Quora, and we’re now bringing those same capabilities to every organization in the world.
Why should you take this role?
Tecton’s ideal customer is an enterprise company that wants to standardize on a single feature store across multiple ML products. Such teams require collaboration, security, governance, compliance, lifecycle management, and system-of-record features to successfully use Tecton across a large number of engineers and data scientists.
By taking on this role, you will be responsible for the success of Tecton in the enterprise. You will specialize in creating a product that goes beyond impacting a handful of people to changing the way large companies build ML applications.
You will be responsible for creating a product moat around Tecton’s commercial offering, giving us predictable revenue growth by taking on these responsibilities:
Responsibilities:
- Own strategy and roadmap of Tecton’s operating environment
- Deliver quality features on time.
- Gather user feedback and usage data.
- Build relationships with enterprise customers and help them be successful on Tecton
- Help product marketing do sales enablement for enterprise features
- Create customer facing training materials for enterprise features
- Advocate Tecton through your writing and speaking
Qualifications:
- 5+ years experience as a Product Manager in enterprise SaaS
- 2+ years experience building enterprise features (collaboration, security governance, compliance, lifecycle management, or system-of-record etc.)
Nice to have:
- 2+ years experience building developer products in general or ML infrastructure in particular, within a company or as SaaS software
.