micro1
micro1Verified listing
RemoteHot

Imagery Analyst - AI/ML Training Data

20–60/hr
Remote
Posted October 7, 2026
contract
10 openings
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Listing checked October 7, 2026 · pay as published by micro1

Overview

micro1 seeks imagery specialists to support a customer project involving drone and maritime sensor data. You will review and correct machine-generated bounding boxes on still images, then label objects the models missed. Work happens inside a secure Navy environment using micro1's own labeling tool. No AI background is needed. Your eye for detail and familiarity with aerial or thermal imagery carry the day. Pay runs from $20 to $60 per hour, and the engagement can be part-time or full-time.

What You'll Do7

  • 1Check machine-drawn bounding boxes on drone and maritime stills, fixing any that are off target.
  • 2Mark objects the AI overlooked, such as vehicles, boats, people, and aircraft.
  • 3Annotate both daylight and thermal sensor captures while following the project's labeling rules.
  • 4Submit finished annotated images through micro1's proprietary application inside a secure Navy setting.
  • 5Keep a steady volume of completed images moving, since pay ties to each submission.
  • 6Shift to labeling video frames once the project scope grows in that direction.
  • 7Flag unclear cases or guideline gaps in writing so the team can resolve them.

Requirements8

  • 1U.S. citizenship is mandatory.
  • 2Ability to obtain a DoD Common Access Card (CAC) or willingness to go through Navy sponsorship.
  • 3Proven focus and consistency on repetitive tasks where accuracy matters.
  • 4Hands-on experience with data labeling, bounding box annotation, or similar data-prep work.
  • 5Comfort reading aerial, maritime, or sensor imagery, including daylight and thermal formats.
  • 6Background in high-volume, quality-controlled annotation settings. Robotics or autonomous-system labeling is a plus.
  • 7Willingness to pick up new labeling software tools.
  • 8Clear written and verbal communication for reporting and clarifying requirements.

Who Should Apply

The right fit is a U.S. citizen who has spent time labeling images, drawing bounding boxes, or preparing sensor data, and who can stay sharp through repetitive, accuracy-critical work. If you have looked at aerial or maritime imagery, especially thermal captures, you will settle in faster. This role is less suited to someone who wants variety or creative freedom in their tasks, or who dislikes working inside strict guidelines. Candidates often get rejected when they cannot show a track record of high-volume annotation with tight quality control, or when they lack the U.S. citizenship and CAC eligibility the project requires.

Salary Insight

The rate is $20 to $60 per hour, with compensation based on each image submission. Final pay depends on your throughput and the project's needs.

Pay and demand for AI Training roles

Aggregated

Typical pay

$70/hour

This role

$20–$60/hr

Most AI Training roles pay $40–$95 per hour. This role's pay falls inside that range.

Based on 984 similar roles that publish pay · 300 publish only a top rate; those count at the rate they gave

Typical rangeMedian payThis role

Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.

Live similar roles
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Most requested skills · share of roles

  • ai evaluation
    14%
  • ai training
    14%
  • llm evaluation
    12%
  • data annotation
    10%

Figures from AI Training roles live on NearSkill when this page loaded. A role can close before you apply, so check the listing itself.

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Location

TypeRemote
LocationRemote
This is a remote position

Compensation

$20–60/hr

Required Skills

Data labelingData annotationLabeling accuracyAttention to detail

Application Tip

In your application, name the exact labeling tools you have used and the volume of images you annotated per day or week. Mention any experience with thermal or aerial sensor data, and confirm your U.S. citizenship and CAC eligibility up front. Those details map directly to the screening criteria.

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