Imagery Analyst / AI/ML Training Data Expert - Remote

Role Type: Contractor – Part-Time or Full-Time
Location: Remote
Eligibility: U.S. Citizenship and Active DoD Common Access Card (CAC) Required

We are seeking detail-oriented Imagery Analysts to contribute to a high-impact AI/ML training project focused on drone and maritime sensor imagery.

In this role, you will apply your imagery analysis and annotation expertise to review AI-generated labels, identify objects, and improve the accuracy of training datasets. Your contributions will help enhance how AI systems interpret and analyze real-world imagery.

No prior AI experience is required. Your subject-matter expertise and attention to detail are what matter.

Important Eligibility Requirements: This project supports a U.S. Navy contract and requires applicants to be U.S. citizens with an active DoD Common Access Card (CAC). Candidates who do not meet these requirements are not eligible for this specific project. However, other annotation opportunities may be available without these restrictions.

1. Review and refine machine-generated bounding boxes to ensure accuracy in still imagery captured by drone and maritime sensors.
2. Identify and annotate objects that have been missed by AI models.
3. Label imagery consistently while following established annotation guidelines.
4. Submit completed annotated images within a secure U.S. Navy project environment.
5. Maintain consistent and reliable productivity, meeting project quality and submission requirements.
6. Transition to video-frame annotation as the project expands.
7. Document and communicate ambiguous cases, annotation challenges, and guideline-related questions clearly.

1. U.S. citizenship and an active DoD Common Access Card (CAC), or eligibility and willingness to participate in the CAC sponsorship process, subject to project requirements.
2. Strong attention to detail and consistency when 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, particularly daylight and thermal imagery.
5. Experience working in high-volume, quality-controlled annotation environments. Robotics or autonomous systems data-labeling experience is an advantage.
6. Comfort using specialized annotation software and willingness to learn new tools.
7. Strong written and verbal communication skills, with the ability to report issues and clarify labeling requirements.