- Robot type
- Drone
- Location
- South San FranciscoCaliforniaUSA
- Job type
- Business Operations
- Posted
- Sep 23, 2026
Droid Autonomy Intern (Summer 2027)
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
- Work hands-on with an autonomous robot operating in the real world — to help expand its capabilities for safer and more reliable deliveries.
- Analyze, validate real-world data to understand system performance and identify failure modes and come up with unique solutions.
- Design experiments and models that improve the robot’s ability to make reliable decisions in highly variable, unpredictable environments .
- Translate insights from validation into actionable improvements that directly impacts the speed, accuracy and safety of the robot delivery.
- Collaborate closely with perception, autonomy, and flight testing teams to see how your work connects across the full robotics stack.
- Gain experience with the end-to-end process of deploying autonomy at scale —from data collection and model development through validation and live operations
- Be part of an extremely motivated team that is delivering real-world solutions at scale, not just research prototypes.
- Work with and iterate on a state-of-the-art autonomous system : analyze flight data, extract key features of the droid’s performance, and identify what it takes to improve motion planning in difficult and uncertain…
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