W logo

Data Annotation Specialist - Computer Vision & Video Labeling

Wealth Recruitment, LLCSan Francisco, CA

$20 - $40 / hour

Automate your job search with Sonara.

Submit 10x as many applications with less effort than one manual application.1

Reclaim your time by letting our AI handle the grunt work of job searching.

We continuously scan millions of openings to find your top matches.

pay-wall

Overview

Schedule
Part-time
Career level
Senior-level
Remote
On-site
Compensation
$20-$40/hour

Job Description

Are you highly detail-oriented with the ability to stay focused through complex visual tasks? We’re seeking a Data Annotation Specialist to support cutting-edge computer vision and autonomous systems development by labeling and reviewing large-scale image and video datasets. In this role, your work will directly improve the quality of machine learning models used in advanced perception systems.

This is an excellent opportunity for candidates with experience in computer vision annotation, robotics, aviation, maritime operations, drone systems, military intelligence analysis, or sensor-based technologies who enjoy analytical, high-focus work in a fast-paced technical environment.

As a Data Annotation Specialist, you will:

  • Perform high-volume image and video labeling using internal proprietary annotation tools
  • Review visual datasets across multiple sensor and data types
  • Identify, document, and flag model failure cases to support machine learning improvements
  • Maintain strong labeling accuracy while meeting throughput and productivity targets
  • Track progress across large datasets and ensure consistent performance
  • Follow established annotation guidelines and escalate unclear or edge-case scenarios when needed
  • Work closely with technical teams to support rapid model development cycles

Requirements

Ideal Background

We’re especially interested in candidates with backgrounds in:

  • Maritime operations
  • Drone/UAS operations
  • Aviation or aircraft systems
  • Military intelligence, ISR, or sensor analysis
  • Robotics or autonomous systems
  • Computer vision or video annotation environments

Required Qualifications

  • Must be a U.S. Citizen (required for CUI eligibility)
  • Experience with computer vision labeling, robotics annotation, or video/image analysis
  • Strong attention to detail and ability to maintain focus during repetitive visual review tasks
  • Comfortable working in proprietary internal software platforms
  • Ability to consistently balance speed and accuracy in a production environment
  • Strong pattern recognition and analytical skills
  • Reliable internet connection and ability to work independently

Benefits

Schedule

  • 20–30 hours per week initially while current project backlog is addressed
  • Hours may adjust based on project needs and performance

Pay Rate = $20 - $40 per hour

Automate your job search with Sonara.

Submit 10x as many applications with less effort than one manual application.

pay-wall

FAQs About Data Annotation Specialist - Computer Vision & Video Labeling Jobs at Wealth Recruitment, LLC

What is the work location for this position at Wealth Recruitment, LLC?
This job at Wealth Recruitment, LLC is located in San Francisco, CA, according to the details provided by the employer. Some roles may also include multiple work locations depending on the requirement.
What pay range can candidates expect for this role at Wealth Recruitment, LLC?
Candidates can expect a pay range of $20–$40 per hour for this role.
What employment applies to this position at Wealth Recruitment, LLC?
Wealth Recruitment, LLC lists this role as a Part-time position.
What experience level is required for this role at Wealth Recruitment, LLC?
Wealth Recruitment, LLC is looking for a candidate with "Senior-level" experience level.
What is the process to apply for this position at Wealth Recruitment, LLC?
You can apply for this role at Wealth Recruitment, LLC either through Sonara's automated application system, which helps you submit applications 10X faster with minimal effort, or by applying manually using the direct link on the job page.