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Flexible Remote Image Annotation Jobs in Virginia

Senior DevSecOps Engineer

Mclean, VA · Remote

$115K - $158K/yr

Built for a remote life Our culture, communications, and tools are built for remote work, enabling ... Embedding security across the pipeline ("shift left"), including SAST, SCA, container and image ...

Web Application Developer

Arlington, VA · On-site +1

$95K - $159K/yr

Familiarity with basic HTML and image optimization. * Understanding of accessibility standards and ... While many positions offer remote or hybrid work options, these arrangements are subject to change ...

Data Engineer

Reston, VA · On-site +1

$119K - $143K/yr

Experience with signal/image processing, geospatial modeling or voice/data communications * Prior ... Financially, we provide flexible spending accounts (FSA), a 401(k) plan with company contributions ...

Data Engineer

Reston, VA · On-site +1

$119K - $143K/yr

Experience with signal/image processing, geospatial modeling or voice/data communications * Prior ... Financially, we provide flexible spending accounts (FSA), a 401(k) plan with company contributions ...

Senior Flight Software Engineer

Reston, VA · On-site +1

$127K - $168K/yr

... image capture, processing, and data exploitation on orbit using embedded hardware. You will also ... Health Savings Account, Flexible Spending Accounts, Dependent Care FSA * Wellness Stipend * Work ...

Flexible Remote Image Annotation information

What is flexible remote image annotation?

Flexible remote image annotation is a job where individuals label or tag elements within digital images from a remote location, often from home. This work is crucial for training artificial intelligence and machine learning models, particularly in fields like computer vision and autonomous vehicles. The 'flexible' aspect means workers can often set their own hours and choose tasks according to their availability. Image annotation tasks may include outlining objects, assigning categories, or describing visual content in images. Most positions require attention to detail and basic computer skills, but prior experience is not always necessary.

What are the key skills and qualifications needed to thrive as a Flexible Remote Image Annotation Specialist, and why are they important?

To thrive as a Flexible Remote Image Annotation Specialist, you need strong attention to detail, visual accuracy, and a basic understanding of image processing, often supported by a high school diploma or equivalent. Familiarity with annotation tools such as Labelbox, CVAT, or VIA, and sometimes experience with basic data entry platforms, is typically required. Excellent time management, communication skills, and the ability to work independently are valued soft skills for this remote role. These skills ensure high-quality, consistent data labeling essential for training reliable machine learning models and supporting AI development.

What are some common challenges faced in flexible remote image annotation roles and how can they be managed?

One common challenge in flexible remote image annotation is maintaining accuracy and consistency across large datasets, especially when guidelines are complex or images are ambiguous. Working independently can also make it harder to get immediate feedback or clarification. To manage these challenges, it’s important to regularly review annotation guidelines, participate in team check-ins or forums, and make use of quality assurance tools provided by the employer. Staying organized and communicating proactively with project leads can help ensure your work meets expectations and deadlines.

What is the difference between Flexible Remote Image Annotation vs Data Labeler?

AspectFlexible Remote Image AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageAI, machine learning, computer visionAI, machine learning, data processing
Job FocusAnnotating images with labels, bounding boxes, segmentationLabeling data, categorizing images or text

Flexible Remote Image Annotation and Data Labeler roles both involve data processing tasks in AI and machine learning industries. While image annotation focuses on marking specific features within images, data labelers may work with various data types, including text and images. Both roles are remote, require similar skills, and serve the same industry needs, but image annotation emphasizes visual data precision.

What are the most commonly searched types of Remote Image Annotation jobs in Virginia? The most popular types of Remote Image Annotation jobs in Virginia are:
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Remote Video Annotators

Barker Staffing Solutions LLC

Hampton, VA • Remote

Full-time

Posted 27 days ago


Job description

Location: Remote (U.S.-based preferred or strong familiarity with U.S. curriculum)
Type: 1099 Contract
Hours: Minimum 40 hours/week
Compensation: Competitive hourly rate based on experience and role

About the Role:

The client is a NYC-based non-profit with a social mission to lift economically and socially marginalized youth out of poverty in Asia and Africa. Using impact-based outsourcing, they create sustainable, living-wage jobs by providing data-labeling and annotation services for training datasets used in Computer Vision and GenAI applications.

The client is seeking dynamic, passionate, detail-oriented, and self-motivated individuals who enjoy providing annotation services. This position is ideal for self-starters with customer-facing etiquette, good communication skills, and a strong work ethic.

Position: Video Annotator (Traffic & Behavioral)

Responsibilities for the Retrieval Benchmark Annotation Project:
Perform multi-dimensional scene annotation for autonomous driving data. As an annotator, go beyond object labeling and perform structured classification, behavioral analysis, and apply causal reasoning.
Apply Advanced Annotation Capability by using the following skills:

Use your experience with annotation tools (segmentation, object tracking, timelines)
Apply complex taxonomies and attribute structures
Deploy accurate frame-level updates and lifecycle management of annotations
Scene Interpretation & Spatial Awareness by using the following skills:
Use your strong understanding of road environments and layouts
Identify road types, traffic infrastructure, and conditions
Demonstrate accurate perception of relative positioning and spatial relationships

Apply Behavioral & Causal Reasoning in the following tasks:

Interpret why events occur, not just what is visible
Identify relationships between ego vehicle, environment, and agents
Create logical links between entities

Apply Temporal Analysis with the following tasks:

Track changes over time within a scene
Update attributes dynamically as scenes evolve

Use Traffic Knowledge & Driving Judgment by using the following skills:

Strong understanding of traffic rules and right-of-way principles
Use discerning ability to assess legal vs illegal and safe vs aggressive behavior

Apply Multi-Agent Interaction Understanding when performing the following tasks:

Analyzing interactions between vehicles, pedestrians, objects, and the environment
Understanding and determining the influence and dependency between actors
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by federal, state, or local laws.

Why Join Us?
  • 100% remote, flexible work scheduled based on the client's needs

  • Be part of a collaborative, mission-driven project
  • Work with a team that values your educational expertise