Data Labeling Specialist, Rwanda [Full Time]

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. As a Data Labeling Specialist, you’ll play a key role in supporting Zipline’s global operations by providing data labeling coverage to ensure continuous, high-quality data processing. You’ll work alongside the broader Autonomy team to review and label data, adding critical contextual metadata for machine learning applications. Our Perception systems rely on accurately labeled data to power safety-critical capabilities such Become an expert in multiple sensor data streams, identifying issues, edge cases, and opportunities to improve labeling and review processes Deliver high quality labeled data on a regular cadence to meet critical timelines and keep algorithm development on track Bachelor’s degree in an engineering field, or have completed all academic requirements including final year coursework and capstone presentations, with graduation pending This position is expected to primarily operate during daytime hou