Drone Systems AI Trainer Specialist
Meridial Marketplace, by Invisible
Job Overview
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Job Description
Drone Systems AI Trainer Specialist at Meridial Marketplace, by Invisible
We are seeking a highly skilled specialist with deep experience in drone systems, drone morphology, or related technical imaging domains to support the development of high-precision computer vision models. This opportunity focuses on the careful interpretation, segmentation, and annotation of drone imagery, with an emphasis on isolating structurally meaningful components of a wide range of unmanned aerial vehicles. The ideal candidate combines a strong technical understanding of drone architecture with an ability to follow nuanced visual-annotation protocols applied consistently across large datasets.
On a typical day, you will evaluate diverse drone images and apply strict annotation standards designed to optimize downstream model performance. A central requirement is the ability to isolate the core structure of a drone while excluding peripheral or transient elements. This includes cropping out rotor blades that introduce undesirable motion artifacts, removing drone legs or stands that are not integral to the aerial frame, ensuring antennas, payloads, and unrelated external objects are not included, and focusing specifically on the drone body, the primary support arms extending from the fuselage, and the electric motors located at the arm extremities. A subtle but essential part of this role is learning to distinguish between structural and non-structural features, especially across varied drone designs, lighting conditions, and environments.
Candidates should bring a high level of visual precision and the ability to assess consistency across large image corpora. Experience with professional or academic work involving drones, robotics imagery, aerial systems, or technical visual datasets is strongly advantageous. Familiarity with annotation platforms, high-resolution image handling, or machine-learning dataset workflows is helpful, though not strictly required; what matters most is a rigorous attention to detail, an ability to operationalize abstract guidelines, and the discipline to apply them without drift as edge cases appear.
If you are motivated by the challenge of transforming complex visual information into structured, high-quality training data—and you take pride in precision, clarity, and conceptual rigor—this opportunity offers the chance to directly shape how advanced AI interprets drone architecture.
We offer a pay range of $6 to $65 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary. As a contractor, you will supply a secure computer and high-speed internet; company-sponsored benefits such as health insurance and PTO do not apply.
Key skills/competency
- Drone Systems
- Computer Vision
- Image Annotation
- Data Labeling
- UAV Morphology
- Technical Imaging
- Robotics Imagery
- Machine Learning Datasets
- Visual Precision
- Attention to Detail
How to Get Hired at Meridial Marketplace, by Invisible
- Research Invisible's AI vision: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor to understand their approach to AI and data quality.
- Tailor your resume: Customize your resume to highlight deep experience in drone systems, computer vision, image annotation, and precise data labeling. Emphasize projects involving UAV morphology and technical visual datasets.
- Showcase visual precision: Prepare a portfolio or examples demonstrating your rigorous attention to detail, ability to follow complex guidelines, and consistency in visual interpretation, especially with drone imagery.
- Highlight relevant experience: Emphasize any professional or academic work with drones, robotics imagery, aerial systems, or machine learning dataset workflows. Demonstrate your capability to operationalize abstract guidelines.
- Ace the technical interview: Be prepared to discuss your understanding of drone architecture, computer vision model requirements, and how to effectively segment and annotate complex visual data.
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