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Zipline

Robot type
Drone
Location
South San FranciscoCaliforniaUSA
Job type
Hardware
Posted
Aug 11, 2026
Salary
$140,000–$230,000 a year
Full-time

Senior/Staff Power Electronics Hardware Reliability Engineer

Job description

Our customers include the world’s largest and most prominent healthcare systems, governments, retailers, restaurants and global businesses who rely on us to save lives, reduce emissions, increase economic opportunity, and provide delivery from point A to point B as fast as possible. The drone is only 15% of what we’ve built to enable seamless, reliable, global operations.

Our system strengthens supply chains, reduces congestion, and gives people time back. With more than 140 million commercial autonomous miles safely flown, Zipline is redefining access to healthcare, consumer products, and food across the globe.

We operate at a global scale and are looking for practical problem solvers who…

Job responsibilities

  • Own the reliability strategy for high-voltage power electronics and power-conversion systems, beginning with Zipline’s grid-connected power converters.
  • Identify and prioritize the dominant reliability risks for high voltage power electronics, considering electrical, thermal, mechanical, environmental, and operational stresses.
  • Lead DFMEA efforts with cross-functional teams to identify early risks and drive mitigation.
  • Evaluate power-electronics architectures, schematics, PCB layouts, component selections, packaging concepts, thermal-management approaches, insulation systems, connectors, and high-current interconnects from a…
  • Develop physics-based Accelerated Life Testing (ALT) and environmental test campaigns to validate long-term hardware performance.
  • Author clear, technically rigorous test plans and specifications, and provide reliability sign-off on test results and hardware readiness.
  • Lead failure analysis and structured root cause investigations, from component to system-level.
  • Define operational life limits and service intervals using a combination of test data, field returns, and statistical models.

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