Head of Weather Systems

Zipline , South San Francisco, California +1

What you will do

Own end-to-end development and operational performance of the automated weather intelligence and risk system used for mission go/no-go decisions across Zipline’s operational regions. You are the single technical and product owner for system behavior and reliability.
Translate meteorological uncertainty into concrete, testable operational limits and encode those into automated decision logic used in daily operations.
Define and measure success: set quantitative targets (e.g., uptime improvement, false downtime rate, missed-risk rate, delivery throughput impact) and deliver within the first 12 months measurable improvements compared with our first year of commercial operations.
Lead validation efforts using a combination of simulation, historical log replay, flight test, and live operations; design experiments and acceptance criteria for new models, sensors, and rules before production rollout.
Prioritize trade-offs across safety margin, operational availability, sensing cost, model complexity, and deployment speed; document failure modes and rollback criteria for all changes.

Zipline , South San Francisco, California +1

Own end-to-end development and operational performance of the automated weather intelligence and risk system used for mission go/no-go decisions across Zipline’s operational regions. You are the single technical and product owner for system behavior and reliability.
Translate meteorological uncertainty into concrete, testable operational limits and encode those into automated decision logic used in daily operations.
Define and measure success: set quantitative targets (e.g., uptime improvement, false downtime rate, missed-risk rate, delivery throughput impact) and deliver within the first 12 months measurable improvements compared with our first year of commercial operations.
Lead validation efforts using a combination of simulation, historical log replay, flight test, and live operations; design experiments and acceptance criteria for new models, sensors, and rules before production rollout.
Prioritize trade-offs across safety margin, operational availability, sensing cost, model complexity, and deployment speed; document failure modes and rollback criteria for all changes.