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.
Tecton's ability to scale and process high volumes of data while being performant and resilient to failures is a key component of the product and central to design decisions. Our team’s data culture is driven by engineers who have worked on major projects such as Google Search and Indexing, Apache Airflow, and Instagram's ML platform.
As an early member of Tecton's engineering team, you will play a critical role in designing, building and scaling our platform. You will leverage your deep experience with cloud architectures, distributed systems, cluster managers like Kubernetes, and Linux system internals to design and build out our hybrid and multi-cloud deployments, ensure our systems are secure in-depth, and scale and optimize our core online serving systems.
Prior experience with machine learning is not required. We are looking for exceptional software engineers who are driven to find simple solutions to complex problems and who are excited to stretch themselves as part of a growing team at the intersection of systems, data, and machine learning.
Bonus points if you have experience with any of the following: distributed systems, batch data processing, stream processing, database internals, query optimizers, query processing, security, machine learning, data science, data integration, recommender systems, information theory, or knowledge graphs.
This position is open to candidates based anywhere in the United States. You have the opportunity to work in one of our hub offices in San Francisco or New York City, or to work fully-remote from outside those areas within the US.