Senior Hardware Reliability Engineer - Field Reliability
About The Position
As a Field Reliability Engineer at Zipline, you will be responsible for measuring, analyzing, and communicating the real-world reliability and economic performance of our deployed drone-delivery systems. You combine experience in data analysis with a working knowledge of Bayesian and classical reliability statistics, applying them pragmatically to the physics of complex failures.Through practical problem-solving, you will ensure Zipline’s aircraft continue to operate safely and reliably in the most demanding environments on Earth. Your work will span the full operation lifecycle from initial product release and early life learning, through identifying and driving targeted reliability improvements, and ultimately end-of-life decisions. You will transform field data into actionable insights by identifying failure trends and quantifying risk. Your reporting will inform data-driven decisions in design, manufacturing, and operation decisions that improve fleet availability, reduce operating cost, and directly influence customer satisfaction.
Requirements
- BS/MS in Mechanical, Electrical, Materials Science, or related field, with 5+ years of experience in reliability, maintenance, or service engineering.
- Proficiency in reliability statistics and modeling: (Weibull/survival analysis, DOE, FMEA, FTA, and reliability growth analysis).
- Skilled in data analysis and scripting tools to analyze large vast datasets and forecast outcomes (Python, Reliasoft, Minitab, JMP, or MATLAB).
Nice To Haves
- Strong communication and leadership skills with a track record of influencing design, manufacturing, and operational decisions across mechanical, electrical, and software disciplines.
- A proactive, systems-level mindset that drives issues to resolution and builds organizational reliability culture.
Responsibilities
- Identify, develop, and maintain metrics for how long products or systems function in the field and verification tests, using measures of time, cycles, or distance (life data) to predict failure.
- Select, develop, and maintain fleet stress and usage metrics using internal data infrastructure to monitor functional performance, predict failure, and recommend intervention.
- Develop and maintain fleet-reliability models that feed into cost and spares planning efforts.
- Create accessibility and visibility of these measures across the business in database tables, dashboards, and reports.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
1,001-5,000 employees
