Imagery Analyst —AI/ML Training Data

Role Title: Imagery Analyst - AI/ML Training Data

Role Type: Contractor — part-time or full-time

Eligibility: This role supports a U.S. Navy project. Under the terms of that federal contract, it requires U.S. citizenship and an active DoD Common Access Card (CAC). Applicants who don’t meet these contract requirements aren’t eligible for this project — but we run other annotation projects without them, so we’d still like to hear from you.

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

1. Review and refine machine-generated bounding boxes for accuracy on still imagery from drone and maritime sensors.
2. Identify and annotate objects missed by AI models.
3. Label data maintaining consistency and adherence to provided guidelines.
4. Deliver completed annotated images within a secure Navy environment
5. Maintain steady, reliable throughput of completed images; compensation is based on each image submission.
6. Transition to annotation of video frames as the project evolves and expands in scope.
7. Document and communicate any ambiguous cases or guideline questions clearly, demonstrating strong written and verbal skills.

Preferred Qualifications

1. U.S. citizenship and ability to obtain a DoD Common Access Card (CAC) or willingness to engage in the sponsorship process.
2. Demonstrated attention to detail and consistency performing repetitive, accuracy-critical tasks.
3. Experience with data labeling, bounding box annotation, or similar data-preparation activities.
4. Familiarity with aerial, maritime, or sensor-based imagery, especially in daylight and thermal formats.
5. Track record in high-volume, quality-controlled annotation environments (robotics or autonomous system data-labeling experience is a plus).
6. Comfort using dedicated software tools for labeling tasks, with a willingness to learn new applications.
7. Strong written and verbal communication skills for reporting and clarifying labeling requirements.