Rwanda-Based Data Annotation Consultant (Full-Time)

Expérience

Lipline stands as the world’s foremost drone delivery service, distinguished by its unparalleled experience and global reach. Committed to equitable access, we deliver essential goods—such as food, medicine, and critical supplies—rapidly and reliably to every corner of the globe. Our autonomous logistics platform, the largest of its kind, powers seamless operations across four continents, executing a delivery every 30 seconds and surpassing millions of completed shipments, including life-saving medical supplies, vaccines, food, and retail products. Trusted by the world’s leading healthcare systems, governments, retailers, and multinational corporations, Lipline enhances supply chains, minimizes congestion, and restores time to communities by redefining logistics from point A to point B with unprecedented speed. Though our drones represent just 15% of our end-to-end system, the remaining infrastructure ensures flawless, scalable operations worldwide—with over 140 million autonomous commercial miles logged safely. We operate at a vast scale, seeking pragmatic problem-solvers who excel in high-stakes, fast-paced environments and are driven by systems that create tangible, life-changing impact. As a Data Labeling Specialist, you will be integral to Lipline’s global autonomy efforts by transforming raw sensor data into precision-labeled datasets that empower our machine-learning models. Your role involves meticulously annotating and reviewing multi-sensor inputs to help our aircraft interpret their surroundings—detecting other aircraft, identifying ground hazards, and ensuring flawless delivery accuracy. You will apply annotation guidelines with rigor, flag edge cases and data inconsistencies, and provide actionable feedback to our Autonomy teams to uphold dataset integrity and accelerate perception development. In this position, you will label and validate data from diverse sensor streams using both internal and external tools, enriching it with essential metadata for machine-learning applications. You’ll cultivate deep expertise across sensor-data workflows, maintain strict adherence to annotation standards, and generate high-quality labeled datasets on a consistent basis to meet critical algorithmic development deadlines. Your responsibilities include diagnosing data anomalies, documenting recurring ambiguities, and escalating tool or process inefficiencies that may compromise labeling accuracy or throughput. Additionally, you will collaborate closely with Autonomy teams to refine labeling tools and workflows, enhancing usability, efficiency, and review precision, while supporting ad hoc projects as needed. To qualify, you must hold a bachelor’s degree in an engineering discipline—or be in your final academic year with graduation pending—and possess

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