Drone Pilot for AI Training and Data Collection

Key Responsibilities:

• Pilot drones equipped with high-resolution cameras, LiDAR, thermal imaging, and other sensors to collect diverse datasets used for training AI algorithms, particularly for autonomous navigation, computer vision, and sensor fusion.
• Capture data in various real-world conditions (e.g., urban, rural, industrial, challenging weather conditions) to expose AI systems to a wide range of environments and scenarios.
• Execute complex drone missions with precise data collection objectives, such as aerial mapping, 3D reconstruction, obstacle detection, and object tracking.
• Collaborate closely with AI engineers, machine learning specialists, and autonomous systems teams to ensure data collection aligns with the specific requirements of AI model training.
• Perform post-flight data quality checks and initial preprocessing to ensure the datasets are ready for use in training AI models.
• Operate drones in both manual and autonomous modes, supporting AI-driven flight operations where drones rely on onboard algorithms for navigation and decision-making.
• Adhere to European Union Aviation Safety Agency (EASA) and local aviation regulations governing drone operations, ensuring the safe and compliant conduct of all drone missions.
• Oversee the maintenance, calibration, and troubleshooting of drones and onboard sensors to ensure the highest standards of performance and reliability.

Qualifications:

• Commercial drone pilot certification (EASA or equivalent), with additional certifications in safety or advanced drone technologies considered a plus.
• Proven track record as a drone pilot, with significant experience in collecting data for industrial, research, or AI-focused applications.
• Expertise in flying drones equipped with advanced sensors such as LiDAR, thermal cameras, RGB cameras, and multispectral sensors.
• Familiarity with the nuances of autonomous flight, sensor integration, and machine learning workflows, especially those that involve real-time data processing.
• Strong understanding of how drone-collected data is used for AI training, including its role in training AI for perception, navigation, and decision-making.
• Experience in using software for flight planning, such as Pix4D, DroneDeploy, or similar platforms, and geospatial data analysis tools.
• Familiarity with machine learning concepts, especially those related to computer vision (e.g., image segmentation, object detection, and tracking) and autonomous navigation systems.
• Basic understanding of geospatial data processing, photogrammetry, and 3D reconstruction techniques for AI applications.
• Strong attention to detail with a commitment to ensuring the highest quality of data collection and analysis.
• Excellent communication and collaboration skills, with the ability to work in multidisciplinary teams.