ABOUT ZIPLINE 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. Today, Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries to date, including blood, vaccines, medical supplies, food, and retail products. 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 thrive on real-world challenges and rapid growth. Our team is motivated by building systems that have a direct, meaningful impact on people’s lives and by scaling the future of logistics. We are seeking people who sculpt from first principles, enjoy facing adversity, and can do the impossible at record breaking speeds. ABOUT THE DROID PLANNING TEAM The Droid Autonomy team owns the entire autonomy stack behind droid package pickup and delivery. This includes perception (understanding the world), high-level decision making (executing behaviors), and motion planning (navigating through obstacles to deliver packages safely and efficiently). It’s an extremely cross-functional team that brings together expertise in robotics, machine learning, planning, and systems engineering—working as one to make the droid a safe, reliable, and scalable real-world delivery system. THE ROLE * 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. WHAT YOU'LL DO * 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 environments. 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'LL BRING * 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. WHAT ELSE YOU SHOULD KNOW The final cash pay for this role will depend on a variety of factors, including a specific candidate's experience, qualifications, skills, and working location. The total compensation package for each role may also include: a housing stipend; overtime pay; relocation support; paid sick time; and more. Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws or our own sensibilities. We value diversity at Zipline and welcome applications from those who are traditionally underrepresented in tech. If you like the sound of this position but are not sure if you are the perfect fit, please apply! Zipline is also committed to providing reasonable accommodations to individuals with disabilities. Please let your point of contact at Zipline know if you require any accommodations throughout your interview process. VOLUNTARY SELF-IDENTIFICATION For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file. As set forth in Zipline ’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

Droid Autonomy Intern (Summer 2027)

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