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Live In Image Annotation Jobs in Washington, DC (NOW HIRING)

Unissant

Data Scientist

Ashburn, VA · On-site

$99K - $164K/yr

Support exploratory data analysis, feature development, image-data preparation, annotation ... Two (2) or more years of experience in data science, computer vision, image analysis, advanced ...

UNISSANT

Data Scientist

Ashburn, VA

Support exploratory data analysis, feature development, image-data preparation, annotation ... Two (2) or more years of experience in data science, computer vision, image analysis, advanced ...

Unissant

Data Scientist

Ashburn, VA · On-site

$99K - $164K/yr

Support exploratory data analysis, feature development, image-data preparation, annotation ... Two (2) or more years of experience in data science, computer vision, image analysis, advanced ...

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All JobsLive In Image Annotation JobsLive In Image Annotation Jobs in Washington, DC

Live In Image Annotation information

What is a live in image annotation?

A Live In Image Annotation job involves residing at a particular location or facility and performing the task of labeling or tagging objects, features, or data within digital images. This work is usually part of larger projects in fields like artificial intelligence, machine learning, or computer vision, where accurately annotated images are crucial for training algorithms. The job may require familiarity with specialized software tools and a keen attention to detail. Annotators play a critical role in helping computers 'see' and understand images by providing clear and consistent labels. Often, these positions are found in research centers, data collection facilities, or companies specializing in AI development.

What are the key skills and qualifications needed to thrive as a live in image annotation specialist?

To thrive as a Live In Image Annotation Specialist, you need strong attention to detail, proficiency in visual analysis, and a basic understanding of data labeling processes, typically supported by a high school diploma or equivalent. Familiarity with annotation tools like Labelbox, CVAT, or Supervisely, and sometimes basic coding knowledge, is often required. Excellent communication, time management, and adaptability are key soft skills for collaborating and meeting project deadlines. These competencies ensure accurate, high-quality data labeling, which is crucial for training reliable machine learning models.

What are some of the common challenges faced by live in image annotation professionals, and how can they be addressed?

Live In Image Annotation professionals often encounter challenges such as maintaining high accuracy while working with large volumes of data, meeting tight deadlines, and handling ambiguous images that require careful judgment. To address these challenges, it's important to stay organized, regularly communicate with team members and project managers, and utilize annotation tools efficiently. Ongoing training and feedback can also help improve both speed and precision, ensuring the quality of annotated data meets industry standards.

What is the difference between Live In Image Annotation vs Image Labeling Specialist?

AspectLive In Image AnnotationImage Labeling Specialist
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentOn-site or remote, often in a dedicated workspaceRemote or on-site, flexible environment
Industry UsageAI training, autonomous vehicles, surveillanceData annotation for machine learning, AI models
Job FocusReal-time annotation, often involving live video or imagesBatch annotation, static images

Live In Image Annotation involves real-time, often on-site annotation of images or videos, suitable for applications like autonomous driving or surveillance. In contrast, Image Labeling Specialists typically perform batch annotation of static images for training AI models, often remotely. Both roles require attention to detail and basic technical skills but differ mainly in real-time versus batch work and work environment.

What are popular job titles related to Live In Image Annotation jobs in Washington, DC?

For Live In Image Annotation jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Live In Image Annotation jobs in Washington, DC look for?

The top searched job categories for Live In Image Annotation jobs in Washington, DC are:

Live In Image Annotation jobs near you
Infographic showing various Live In Image Annotation job openings in Washington, DC as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 71% Full Time, 25% Part Time, and 2% Contract. Highlights an 84% Physical, 1% Hybrid, and 15% Remote job distribution.

Data Processor

Vienna, VA • On-site

Silent Falcon UAS Technologies
11 - 50 employees
Learn more about Silent Falcon UAS Technologiesexternal

Full-time

Re-posted 22 days ago

Job description

Job Summary:
Silent Falcon UAS Technologies is at the forefront of AI and digital twins innovation for airports and transportation infrastructure. They are seeking a Data Processor to support AI Engineers by preparing, annotating, and validating high-resolution remote sensing datasets to ensure model accuracy and usability for clients.
Responsibilities:
• Process, clean, and annotate image data, 3D scan data, point clouds, or mesh data (marking cracks, distresses, edge lines, etc.)
• Organize and maintain datasets, metadata, and geolocation tags to ensure data is properly georeferenced.
• Validate model predictions, help with error review, and flag data anomalies or misclassifications.
• Assist in preparing datasets for training, testing, and temporal/change-detection comparisons.
• Follow data quality standards, maintain consistency across annotators.
• Work with the AI Engineer to refine annotations tools, guidelines, and workflows.
Qualifications:
Required:
• Bachelors degree (in progress or completed) in Computer Science or related field.
• 1+ years of relevant experience.
• Experience with image annotation tools or similar platforms.
• Ability to identify cracks, pavement distresses, and texture changes in imagery.
• Comfortable working with large file sizes.
• Strong organizational skills.
• Strong attention to detail.
Preferred:
• Basic familiarity with geospatial concepts (coordinates) is a plus.
Company:
SF is using proprietary generative AI and predictive analytics to lower airport management cost and improve safety. Founded in 2010, the company is headquartered in Front Royal, USA, with a team of 11-50 employees. The company is currently Early Stage.

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