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Imagery Analyst - AI/ML Training Data
- Location
- Remote, US-based.
- Pay listed by micro1
- $20–60 per hour
- Field
- Generalist
- Type
- Remote
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Role description
Copied from micro1's job page on 9 October 2026. The live page on micro1 is the one that counts.
Role Title: Imagery Analyst - AI/ML Training Data
Role Type: Contractor (Part-time or Full-time)
Location: Remote, US-based.
micro1 is engaging Imagery Analyst - AI/ML Training Data experts to contribute to a high-impact customer project centered on drone and maritime sensor imagery. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
Scope of Work
- Review and refine machine-generated bounding boxes for accuracy on still imagery from drone and maritime sensors.
- Identify and annotate objects missed by AI models.
- Label data maintaining consistency and adherence to provided guidelines.
- Deliver completed annotated images within a secure Navy environment
- Maintain steady, reliable throughput of completed images; compensation is based on each image submission.
- Transition to annotation of video frames as the project evolves and expands in scope.
- Document and communicate any ambiguous cases or guideline questions clearly, demonstrating strong written and verbal skills.
Preferred Qualifications
- U.S. citizenship and ability to obtain a DoD Common Access Card (CAC) or willingness to engage in the sponsorship process.
- Demonstrated attention to detail and consistency performing repetitive, accuracy-critical tasks.
- Experience with data labeling, bounding box annotation, or similar data-preparation activities.
- Familiarity with aerial, maritime, or sensor-based imagery, especially in daylight and thermal formats.
- Track record in high-volume, quality-controlled annotation environments (robotics or autonomous system data-labeling experience is a plus).
- Comfort using dedicated software tools for labeling tasks, with a willingness to learn new applications.
- Strong written and verbal communication skills for reporting and clarifying labeling requirements.
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