Senior Manager, Data Platform & Autonomy Infrastructure

Senior Manager, Data Platform & Autonomy Infrastructure

San Francisco Bay Area — In Person

About Zipline

Zipline is building the world’s first instant logistics system. Using autonomous aircraft, we deliver critical and everyday goods to people when and where they need them. Today, Zipline operates the largest autonomous delivery network in the world, supporting healthcare systems, governments, and commercial partners across multiple continents.

As Zipline scales from tens of thousands to millions of flights per day, data becomes core infrastructure. The systems that decide what data we collect, how we process it, and how teams learn from it directly impact safety, autonomy performance, uptime, and cost.

About the Role

Zipline is hiring a Senior Manager, Data Platform & Autonomy Infrastructure to lead the teams and systems that turn real-world flight data into learning and action.

This role owns the end-to-end data platform for autonomy and operations—from onboard logging and ingestion, to postprocessing, sampling, and curated datasets used by autonomy, hardware, operations, and business teams.

You will set technical direction, build and lead the organization, and ensure these systems operate reliably at >1 million flights per day with high uptime. This role is a strong fit for leaders who have built large-scale robotics or autonomy data systems in production environments.

This role is in person and based in the San Francisco Bay Area.

What You’ll Do

Set Technical Direction

•

Define the long-term strategy and roadmap for Zipline’s data, autonomy, and ML-enabling infrastructure

•

Establish architectural standards across logging, ingestion, processing, storage, access/visualization, and ML training and evaluation

•

Balance reliability, performance, cost, and developer productivity across the platform

•

Support a diverse set of internal customers, including hardware teams, autonomy/software teams, and analytics/business teams

Enable Debugging, Learning, and Scale

•

Support rapid root-cause analysis across autonomy, hardware, and operations

•

Partner with autonomy and validation teams to close the loop between real-world data and development

•

Design systems that scale beyond 1 million flights per day without linear growth in cost or operational complexity

Own Autonomy Data, Logging, and Sampling

•

Set direction and accountability for onboard and offboard data logging systems

•

Make principled decisions about what data to collect, retain, and prioritize under bandwidth, storage, and cost constraints

•

Lead development of tooling to identify rare, novel, and safety-relevant scenarios from large-scale flight data

•

Define sampling strategies that maximize signal for autonomy evaluation, simulation, and ML training

Build ML Infrastructure Foundations

•

Build and operate infrastructure that supports reproducible training and evaluation for autonomy ML workflows

•

Enable scalable pipelines for dataset generation, experiment tracking, and offline evaluation

•

Establish strong reliability, observability, and operational practices for ML data flows and evaluation runs

What You’ll Bring

• 10+ years of experience building large-scale data, infrastructure, or autonomy-adjacent systems

• Experience leading senior engineers or multiple teams

• Strong background in robotics, autonomy, logistics, or other data-intensive physical systems

• Deep understanding of logging, ingestion, processing, and data platform architecture

• Experience working in environments where data is safety-critical, expensive, and operationally constrained

• Strong communication skills and sound technical judgment

Why This Role Matters

This role owns how Zipline learns from the real world.

The Senior Manager, Data Platform & Autonomy Infrastructure builds the systems that turn millions of flights into faster autonomy improvement, safer operations, and a scalable, profitable business.

If you want to work on data systems at the intersection of robotics, autonomy, and real-world impact—this is a rare opportunity.