- Where
- South San Francisco, California, USA
- Posted
- Today
Apply data analysis, statistics, and machine learning techniques to increase the reliability and robustness of the droid’s deliveries.
Design and run validation experiments to measure success and failure rates under different real-world conditions (e.g., driveway geometry, car presence, time of day).
Develop tools and pipelines to evaluate motion planning models, quantify uncertainty, and connect improvements directly to field performance.
What you'd do
- Currently pursuing a Master’s in CS, EE, Robotics, or a related field with a familiarity with learning-based planning methods.
- Software Proficiency and the ability to write safe and performant code; willing to learn new languages and adapt.
- Statistical reasoning & validation mindset: able to design experiments, account for bias/variance, quantify confidence, and interpret results to guide decisions.
- Structured problem solver: can break ambiguous, real-world problems into hypotheses and executable plans; comfortable making and testing assumptions.
- Able to work in person at our office and thrive in a collaborative, hands-on environment.
About Zipline · 2027 Internships
Zipline is the world’s largest and most experienced drone delivery service. We are on a mission to serve all humans equally by ensuring access to food, medicine and essential goods anytime, anywhere. We design, build, and operate the world’s largest autonomous logistics system, delivering critical supplies quickly and reliably.