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Develop and deploy computer vision and perception systems for autonomous aerial platforms. Responsibilities include object detection, tracking, classification, SLAM, 3D world modeling, semantic scene understanding, multi-agent perception, sensor fusion, and GNSS-denied operation. The engineer will take algorithms from simulation through live flight testing and production, optimize them for real-time edge hardware, and collaborate with flight controllers, systems engineers, and operations teams.

Own and develop the Android control application for commanding autonomous drone fleets. Responsibilities include architecture, real-time UI development for telemetry, video, maps, and fleet status; networking over UDP, TCP, WebSockets, and custom protocols; performance optimization; offline and degraded-connectivity support; and collaboration with pilots, operators, backend engineers, and integration teams.

Own end-to-end integration of drones, robotics platforms, sensors, payloads, and third-party hardware. Design circuits and PCBs, develop embedded firmware and integration tooling, debug hardware/software/networking issues, and execute HIL, simulation, laboratory, and field validation. Collaborate with OEMs, vendors, and cross-functional engineering teams to deliver reliable, production-ready autonomous systems.

Integrate drones, sensors, payloads and third-party software into a fleet management platform. Write production-quality Java, C++, and Python code, debug across software, networking and hardware, test in simulation, lab and field, and own end-to-end integrations with vendors, pilots, and product teams.