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Ai Annotation Remote Jobs in Virginia (NOW HIRING)

This role blends remote sensing science with applied data engineering and AI. What You'll Do ... Support annotation workflows by identifying and flagging imagery containing objects of interest

This role blends remote sensing science with applied data engineering and AI. What You'll Do ... Support annotation workflows by identifying and flagging imagery containing objects of interest

This role blends remote sensing science with applied data engineering and AI. What You'll Do ... Support annotation workflows by identifying and flagging imagery containing objects of interest

Showing results 21-23

Ai Annotation Remote information

Are AI annotation jobs legit?

AI annotation jobs are legitimate positions involving labeling data for machine learning models, often requiring attention to detail and familiarity with annotation tools. They are commonly remote, part-time or freelance, and may require basic training or certification. However, job seekers should verify the employer's credibility to avoid scams.

How to become an AI annotation remote?

To become an AI annotation remote worker, you should have strong attention to detail, basic computer skills, and familiarity with annotation tools or platforms. Many positions require a high school diploma or equivalent, and some may ask for prior experience in data labeling or related tasks. Applying through online job boards and demonstrating accuracy and reliability can help secure remote annotation roles in AI development.

What are the most common challenges faced by remote AI annotation specialists, and how can they be effectively managed?

Remote AI annotation specialists often encounter challenges such as maintaining consistent data quality, managing repetitive tasks, and communicating effectively with geographically dispersed teams. To overcome these issues, it's important to establish clear annotation guidelines, participate in regular team check-ins, and use collaboration tools for feedback and support. Utilizing productivity techniques and taking scheduled breaks can also help maintain focus and accuracy throughout the workday.

What are the key skills and qualifications needed to thrive as an AI annotation remote worker?

To thrive as an AI Annotation Remote Worker, you need strong attention to detail, data labeling accuracy, and familiarity with basic computer operations, often supported by a high school diploma or higher. Experience with annotation platforms, image/video labeling tools, and understanding of data privacy protocols are typically required. Excellent communication, time management, and the ability to follow detailed instructions help individuals excel in this role. These skills ensure high-quality, precise data labeling that directly impacts the effectiveness of AI models.

What is an AI annotation remote job?

AI Annotation Remote jobs involve labeling, categorizing, or tagging data such as images, videos, text, or audio to train artificial intelligence and machine learning models. These tasks are typically performed from home using a computer and specialized annotation tools provided by employers or platforms. The work helps improve the accuracy of AI systems in areas like speech recognition, computer vision, and natural language processing. It is common for these positions to be part-time or contract-based, and attention to detail is essential for success in this field.

What is the difference between Ai Annotation Remote vs Data Labeler?

AspectAi Annotation RemoteData Labeler
Required CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote or on-site, flexible hours
Industry UsageAI development, machine learning projectsData preparation, machine learning datasets
Search & Comparison IntentOften compared for entry-level AI data tasksRelated role for data preparation tasks

Ai Annotation Remote and Data Labeler roles share similar requirements and work environments, focusing on data annotation for AI systems. However, Ai Annotation Remote often emphasizes more specialized tasks within AI development, while Data Labeler roles may include broader data preparation activities. Both are suitable for remote work and require attention to detail, making them popular choices for those entering the AI industry.

What are the most commonly searched types of Ai Annotation jobs in Virginia? The most popular types of Ai Annotation jobs in Virginia are:
What cities in Virginia are hiring for Ai Annotation Remote jobs? Cities in Virginia with the most Ai Annotation Remote job openings:
Infographic showing various Ai Annotation Remote job openings in Virginia as of August 2026, with employment types broken down into 73% Full Time, 23% Part Time, and 4% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution.

Senior SAR Imagery Scientist

GeoYeti

Springfield, VA • Remote

$190K - $235K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago


Job description

Senior SAR Imagery Scientist

Springfield, VA or St. Louis, MO

Active TS/SCI eligibility with eligibility to obtain CI poly

At Bcore, our strength comes from how we deliver impact to the mission. Whether it’s architecting critical IT solutions, producing actionable intelligence, or developing cutting edge technology, we succeed because of the expertise, collaboration, and agility of our teams. Our Insight Solutions division delivers intelligence analysis, advanced data science, and strategic decision support. Bcore accelerates decisive advantage for warfighters and intelligence professionals by fusing human insight, rapid-fire engineering, precision-measured outcomes, and relentless grit into mission-ready solutions. 

Are you ready to lean into analytic approaches that show customers the power of both technical and methodological innovation? Join our growing team supporting customer missions as a Senior SAR Imagery Analyst in Springfield, VA or St. Louis, MO.


You will serve as the technical lead on SAR data quality, sensor integration, and imagery processing. You will building automated pipelines, assessing new sensors, and developing algorithms that support analysis at scale. This role blends remote sensing science with applied data engineering and AI.

What You'll Do: 

  • Evaluate and integrate new SAR sensors and platforms into existing data workflows, including sensors still in early development phases
  • Assess differences between new and existing sensors including data formats, metadata structures, and processing requirements and determine changes needed for downstream use
  • Pre-process, standardize, and tile imagery to specified formats and dimensions while preserving data integrity
  • Develop conversion models to transform data across imagery formats and coordinate systems, ensuring geospatial accuracy
  • Analyze image quality and sensor metadata to guide imagery acquisition and curation priorities
  • Build automated methods to manage and curate large imagery datasets, including integrating with external data sources via APIs
  • Support annotation workflows by identifying and flagging imagery containing objects of interest
  • Source complementary imagery from other sensors to support multi-modal analysis
  • Develop, test, and evaluate new algorithms and processing workflows using Python, MATLAB, or similar tools
  • Manage routine and ad-hoc imagery delivery operations
  • Communicate technical findings and capabilities to both technical and non-technical audiences

Required Qualifications:   

  • Active TS/SCI eligibility with eligibility to obtain CI poly
  • 4+ years of hands-on SAR expertise, including collection, phenomenology, image formation, and exploitation
  • Experience with SARPy and/or MATLAB SAR toolbox
  • Familiarity with SAR image quality assessment methods and sensor metadata
  • Understanding of how geometry affects SAR phenomenology (e.g., graze angle, squint, azimuth)
  • Experience exploiting SAR imagery for object detection and characterization
  • Experience developing and automating geospatial or imagery processing workflows
  • Strong foundation in remote sensing principles and geospatial data processing
  • Clear communicator across technical and non-technical audiences

Desired Qualifications:  

  • Experience applying machine learning or computer vision techniques to SAR or other remotely sensed data
  • Experience working with multi-sensor or multi-modal imagery (e.g., SAR and EO)
  • Familiarity with cloud-based geospatial processing platforms

  • The expected salary range within the Washington, DC metropolitan area is: $190,000-$235,000. Final compensation is unique to each individual and will be determined based on factors such as experience, education, geographic location, and contractual requirements. This is not a guarantee.
  • Benefits include Health/Dental/Vision, 401(k), Paid Time Off, STD/LTD/Life Insurance/Voluntary Life Insurance, Stipends, Referral Bonuses, and more.

BCore is proud to be an equal opportunity workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, sexual orientation or any other characteristic protected by law.