About the job
Senior Manager of Data Platforms & Autonomy Infrastructure
San Francisco Bay Area — In Person
About Zipline
Zipline is pioneering an innovative instant logistics system, utilizing autonomous aircraft to deliver essential and everyday items to individuals precisely when and where they need them. Currently, Zipline boasts the world's largest autonomous delivery network, providing support to healthcare systems, governmental agencies, and commercial partners across various continents.
As Zipline expands its operations from tens of thousands to millions of flights daily, the significance of data as core infrastructure cannot be overstated. The mechanisms that determine the data we gather, how we process it, and how teams utilize it directly influence safety, autonomy performance, system uptime, and operational costs.
About the Role
We are seeking a Senior Manager of Data Platforms & Autonomy Infrastructure to spearhead teams and systems that transform real-world flight data into actionable insights and learning experiences.
This pivotal role is responsible for the comprehensive data platform for autonomy and operations, overseeing everything from onboard data logging and ingestion to post-processing, sampling, and the creation of curated datasets utilized by autonomy, hardware, operations, and business teams.
The ideal candidate will establish technical direction, build and guide the organization, and ensure the reliability of these systems to accommodate 1 million flights daily with exceptional uptime. This position is particularly suited for leaders who have experience in developing large-scale robotics or autonomy data systems in production environments.
This is an in-person position based in the San Francisco Bay Area.
Key Responsibilities
Set Technical Direction
Develop a long-term strategy and roadmap for Zipline’s data, autonomy, and machine learning infrastructure.
Establish architectural standards across logging, data ingestion, processing, storage, access/visualization, and machine learning training and evaluation.
Balance reliability, performance, cost, and developer productivity across the platform.
Support a diverse range of internal stakeholders, including hardware teams, autonomy/software teams, and analytics/business teams.
Facilitate Debugging, Learning, and Scalability
Enable swift root-cause analysis across autonomy, hardware, and operations.

