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.