Autonomy Zip Perception SWE

Zipline is a drone delivery company building and operating an autonomous logistics system for delivering essential goods. The Senior Machine Learning and Perception Engineer will develop aircraft and obstacle detection and tracking systems, build reliable vision and model-training infrastructure, and improve the safety and performance of autonomous navigation in real-world environments.

Responsibilities:

• Advance the Frontiers of Perception: Design and deploy cutting-edge algorithms to detect, localize, and track aircraft and tall obstacles using monocular and multi-view camera systems — combining deep learning with geometric vision to achieve robust 3D situational awareness at scale
• Engineer Reliable Vision Systems: Develop scalable model training pipelines and build rigorous evaluation frameworks that capture real-world performance across edge cases and long-tail scenarios
• Integrate Across Systems: Collaborate with systems, flight test, and validation teams to design end-to-end test plans that push perception to the edge of capability — and beyond Zipline’s strict safety and reliability standards
• Own Operational Performance: Create powerful debugging, visualization, and analysis tools that drive insight from field data, enabling rapid triage and root-cause analysis of perception issues in live deployments
• Learn Fast, Iterate Faster: Leverage simulation and real-world feedback to continuously refine both ML models and classical tracking algorithms — improving accuracy, latency, and robustness in challenging operational conditions
• Set the Standard for Airspace Autonomy: Contribute to the long-term vision and architecture of Zipline’s detect-and-avoid system, helping shape a perception stack that leads the industry in safety, reliability, and autonomy