Imagery Analyst —Imagery Analyst - AI/ML Training Data

$30–60/hr

rate as listed

Workload: ~15h/week
Engagement: Project-based
Location: US
Field: STEM and Coding

Review drone and maritime sensor imagery, correct machine-generated bounding boxes, and annotate objects the model missed. This remote, United States-based contract supports still-image labeling now and may expand to video-frame annotation.

The work

You will review still imagery from drone and maritime sensors, refine machine-generated bounding boxes, add annotations for missed objects, and apply the provided labeling guidelines consistently. The workflow also requires documenting ambiguous cases and delivering completed images through a secure Navy environment. As the project develops, assignments may expand to video frames.

What the platform screens for

The screen is likely to focus on concrete examples of accuracy-critical imagery work, including how you find missed objects, handle uncertain targets, and keep bounding boxes consistent across daylight and thermal imagery. Experience with data labeling, aerial or maritime imagery, high-volume quality control, robotics, or autonomous-system datasets is preferred. Prior AI experience is not required.

Practical details

This is a remote, United States-based contractor role available on a part-time or full-time basis. The listing does not specify fixed weekly hours or confirm fully async scheduling, and compensation is described as being based on each submitted image. Access to a secure Navy environment is part of the workflow, while United States citizenship and the ability to obtain a DoD Common Access Card, or willingness to enter the sponsorship process, are preferred. Pay band: $30–60/hr

What they look for

Data labeling
Data annotation
Labeling accuracy
Attention to detail

Included with this listing

Interview prep — 10 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: This tests whether your imagery background is verifiable and relevant to the sensor perspectives, object scales, and image conditions in this project.
A strong answer: Give a specific project, employer, dataset, or operational context, then identify the imagery type, your exact task, the tools used, and how quality was measured. Distinguish direct annotation experience from adjacent imagery-analysis work.
Where people lose it: Candidates lose points by saying they have worked with imagery without naming the sensor format, target types, annotation task, or deliverables.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.

STEM AND CODING on Sidequest

What stem and coding AI work pays

Rates by specialty, the platforms hiring, and every open role in this field.