채용

Senior Manager, Data Platform & Autonomy Infrastructure
South San Francisco, California, USA
·
On-site
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Full-time
·
1mo ago
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
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10+ years of experience building large-scale data, infrastructure, or autonomy-adjacent systems
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Experience leading senior engineers or multiple teams
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Strong background in robotics, autonomy, logistics, or other data-intensive physical systems
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Deep understanding of logging, ingestion, processing, and data platform architecture
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Experience working in environments where data is safety-critical, expensive, and operationally constrained
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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.
What Else You Need to Know
The starting cash range for this role is $225,000 - $275,000. Please note that this is a target, starting cash range for a candidate who meets the minimum qualifications for this role. The final cash pay for this role will depend on a variety of factors, including a specific candidate's experience, qualifications, skills, working location, and projected impact. The total compensation package for this role may also include: equity compensation; discretionary annual or performance bonuses; sales incentives; benefits such as medical, dental and vision insurance; paid time off; and more.
Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, ancestry, national origin, religion or religious creed, mental or physical disability, medical condition, genetic information, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, gender expression, age, marital status, military or veteran status, citizenship, or other characteristics protected by state, federal or local law or our other policies.
We value diversity at Zipline and welcome applications from those who are traditionally underrepresented in tech. If you like the sound of this position but are not sure if you are the perfect fit, please apply!
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Zipline 소개

Zipline
Series DZipline International Inc. is an American company that designs, manufactures, and operates delivery drones, with distribution centers in the United States, Rwanda, Ghana, Japan, Nigeria, Côte d'Ivoire, and Kenya.
201-500
직원 수
San Francisco
본사 위치
$2.7B
기업 가치
리뷰
3.8
10개 리뷰
워라밸
3.2
보상
4.0
문화
4.1
커리어
3.5
경영진
2.8
68%
친구에게 추천
장점
Great learning opportunities and experience
Supportive and collaborative team environment
Good benefits and competitive salary
단점
High stress and demanding workload
Limited career advancement opportunities
Inconsistent management and leadership
연봉 정보
7개 데이터
Mid/L4
Mid/L4 · Analytics Engineer
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-
$221,000
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