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Contract Data Labeler Jobs in Virginia (NOW HIRING)

Kellton

Level 3 Data Center Installers

Ashburn, VA · On-site

$35/hr

Ashburn, VA Duration - 6 months + Contract Pay Rate: $35/hr W2 (No Benefits) Shift - 7AM- 3PM ... Mount and label a wide variety of telecommunication units, terminal blocks, and interconnect panels.

GRVTY

Imagery Scientist (SAR) - Expert

Falls Church, VA

$180K - $210K/yr

Transform data labels across multiple imagery types (e.g., phase history data to complex image and ... federal contract labor categories, wage rates, prior experience, skillsets, education, and ...

GRVTY

Imagery Scientist (EO) - Expert

Falls Church, VA · On-site

$180K - $210K/yr

Transform data labels across multiple imagery types * Convert between orthorectified and non ... federal contract labor categories, wage rates, prior experience, skillsets, education, and ...

GRVTY

Imagery Scientist (SAR) - Expert

Falls Church, VA · On-site

$180K - $210K/yr

Transform data labels across multiple imagery types (e.g., phase history data to complex image and ... federal contract labor categories, wage rates, prior experience, skillsets, education, and ...

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All JobsContract Data Labeler JobsContract Data Labeler Jobs in Virginia

Contract Data Labeler information

What is the difference between Contract Data Labeler vs Data Annotator?

AspectContract Data LabelerData Annotator
CredentialsHigh school diploma or equivalent; basic computer skillsHigh school diploma or equivalent; attention to detail
Work EnvironmentRemote or on-site; tech companies, AI firmsRemote or on-site; AI and machine learning projects
Industry UsageUsed in AI training, machine learning datasetsUsed in AI, computer vision, NLP projects
Job FocusLabeling data for machine learning modelsAnnotating data to improve AI algorithms

The Contract Data Labeler and Data Annotator roles are similar, both involve labeling data for AI training. The main difference lies in terminology and specific project focus, but they often share similar credentials, work environments, and industry applications.

What are the key skills and qualifications needed to thrive as a Contract Data Labeler, and why are they important?

To thrive as a Contract Data Labeler, you need strong attention to detail, accuracy, and basic data management skills, often supported by a high school diploma or equivalent. Familiarity with data annotation tools, spreadsheet software, and sometimes project management platforms is typically required. Excellent focus, time management, and the ability to follow detailed instructions are crucial soft skills in this role. These skills ensure labeled data is reliable and consistent, which is vital for training high-quality AI and machine learning models.

What are some common challenges faced by Contract Data Labelers, and how can they be addressed?

Contract Data Labelers often work with large volumes of diverse data, which can lead to repetitive tasks and fatigue. Ensuring accuracy and consistency in labeling is crucial, as errors can significantly impact machine learning outcomes. To address these challenges, it's important to take regular breaks, follow detailed guidelines, and communicate with team members or project leads when ambiguities arise. Many teams use quality assurance checks and feedback sessions to help labelers maintain high standards and continuously improve their work.

What are contract data labelers?

Contract data labelers are professionals hired on a temporary or project basis to annotate and categorize data, such as images, text, or audio, for use in machine learning and artificial intelligence projects. Their main responsibility is to accurately tag or label data according to specific guidelines so that algorithms can learn to recognize patterns. As contractors, they typically work remotely and are paid per task, hour, or project. This role is essential for companies developing AI models that require large sets of accurately labeled data.
What are the most commonly searched types of Data Labeler jobs in Virginia? The most popular types of Data Labeler jobs in Virginia are:
What are popular job titles related to Contract Data Labeler jobs in Virginia? For Contract Data Labeler jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Contract Data Labeler jobs in Virginia look for? The top searched job categories for Contract Data Labeler jobs in Virginia are:
What cities in Virginia are hiring for Contract Data Labeler jobs? Cities in Virginia with the most Contract Data Labeler job openings:
Contract Data Labeler jobs near you
AI Data Collector - Computer Vision (Remote/Contract)

AI Data Collector - Computer Vision (Remote/Contract)

micro1 AI

Chesapeake, VA • Remote

$13/hr

Part-time

Posted 22 days ago

Job description

Job Title: Data-Video Generalist


Job Type: Contractor


Location: Remote - experts based in Alabama, Arkansas, Georgia, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Mississippi, Montana, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Utah, Virginia, West Virginia, and Wisconsin.


Job Summary: 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.


Key Responsibilities:

  1. Capture precise motion data using your smartphone during specified physical tasks.
  2. Supported devices include the iPhone 12 and later, Google Pixel 6 and later, and Samsung Galaxy S21 and later.
  3. Record synchronized video footage to validate and enhance the integrity of collected sensor data.
  4. Follow detailed technical protocols to ensure all submissions meet strict quality, labeling, and determinism standards.
  5. Consistently contribute a minimum of 10 hours of approved video data per week throughout the project duration.
  6. Communicate effectively with the team to clarify guidelines and provide feedback on data collection processes.
  7. Ensure timely and reliable delivery of data outputs in accordance with project milestones.
  8. Participate in required device compatibility checks and a custom AI-enabled interview process.


Required Skills and Qualifications:

  1. Access to a head strap to be able to record both hands within 48 hours of the start date.
  2. Demonstrated adherence to standardized protocols and rigorous technical instructions.
  3. Proven ability to manage and deliver reliable output in a fast-paced, data-driven environment.
  4. Strong written and verbal communication skills; ability to document work and collaborate remotely.
  5. Experience with mobile devices and a high level of digital literacy.
  6. Physical capability to perform repetitive movement tasks safely and accurately.
  7. Access to a compatible smartphone for high-fidelity sensor and video data collection.
  8. Eligibility to work in designated U.S. states.
  9. Note: Applications submitted with a Gmail address are strongly preferred for seamless tool integration.


Compensation Structure

Compensation is output-based; experts are paid per recorded video that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow.


Start Timeline & Availability

We typically fill roles within 48 hours, so we’re looking for teammates who are ready to jump in. If selected, we’d love for you to start your first task as soon as you move forward with your application. The expectation is to begin within ~24 hours of completing onboarding.


Equipment Requirements

Mobile:

Tasks for this project must be performed from a mobile device (smartphone). Experts will record their workflow directly from the mobile device while completing tasks.


Head Strap / Wearable: Tasks for this project must be performed using a head-mounted camera (head strap setup). Experts will record first-person video of physical tasks. The required head strap and any accompanying equipment specifications will be shared during onboarding.

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