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Seasonal Remote Data Annotation Jobs in Virginia

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

Collaborate with the Data QA team to define annotation standards, resolve taxonomy issues, and ... Experience working with remote sensing imagery including geometry, radiometric normalization ...

We are open to considering fully remote applicants. Dewberry is a leading, market-facing ... Manage ORD and OBM data environments and model health , including information governance strategy ...

This is a remote position with approximately 25% of travel required. Travel includes visits to our ... Background within Home Décor, Garden, Outdoor Living, Seasonal, Gift, Housewares, or related ...

National Account Sales Manager

Richmond, VA · On-site +1

$100K - $300K/yr

This is a remote position with approximately 25% of travel required. Travel includes visits to our ... Background within Home Décor, Garden, Outdoor Living, Seasonal, Gift, Housewares, or related ...

Showing results 21-35

Seasonal Remote Data Annotation information

What are the key skills and qualifications needed to thrive as a seasonal remote data annotation specialist?

To thrive as a Seasonal Remote Data Annotation Specialist, you need strong attention to detail, basic computer literacy, and the ability to follow complex guidelines, typically supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling tools, and sometimes specialized software like image or text tagging systems is often required. Excellent time management, self-motivation, and clear written communication are critical soft skills for remote work success. These abilities ensure high-quality, accurate data output that supports machine learning projects and meets project deadlines.

What are some common challenges faced in a seasonal remote data annotation role, and how can they be managed?

Seasonal remote data annotation roles often require adapting quickly to fluctuating workloads and new annotation guidelines as projects change. Job seekers may find it challenging to maintain consistent accuracy and productivity while working independently from home, especially when handling repetitive tasks. To manage these challenges, it's helpful to establish a structured daily routine, stay updated on project instructions, and actively communicate with team leads or fellow annotators for clarification. Additionally, utilizing project management tools and regularly reviewing feedback can help maintain high-quality output throughout the season.

What is the difference between Seasonal Remote Data Annotation vs Data Labeling Specialist?

AspectSeasonal Remote Data AnnotationData Labeling Specialist
CredentialsBasic computer skills, attention to detailSimilar credentials, often with familiarity in labeling tools
Work EnvironmentRemote, project-based, seasonalRemote or on-site, ongoing or project-based
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, computer vision
Search IntentSeasonal remote data annotation jobsData labeling jobs

Seasonal Remote Data Annotation involves short-term, project-based tasks focused on annotating data for AI models, often during peak seasons. Data Labeling Specialists may work year-round, providing ongoing data annotation services. While both roles require similar skills and tools, Seasonal Remote Data Annotation is typically temporary and tied to specific projects, whereas Data Labeling Specialists may have more continuous responsibilities.

What is a seasonal remote data annotation job?

Seasonal remote data annotation jobs involve labeling and categorizing data—such as images, text, or audio—from home during busy periods when companies need extra help. These positions are typically temporary and align with peak business seasons or special projects. Data annotation is essential for training artificial intelligence and machine learning models to accurately interpret information. Working remotely in this role allows for flexible hours and the ability to contribute from anywhere with a reliable internet connection.

What are popular job titles related to Seasonal Remote Data Annotation jobs in Virginia?

For Seasonal Remote Data Annotation jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Seasonal Remote Data Annotation jobs in Virginia look for?

The top searched job categories for Seasonal Remote Data Annotation jobs in Virginia are:

What cities in Virginia are hiring for Seasonal Remote Data Annotation jobs?

Cities in Virginia with the most Seasonal Remote Data Annotation job openings:

Senior SAR Imagery Scientist

GeoYeti

Springfield, VA • Remote

$190K - $235K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 10 days ago


Job description

Overview

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.

Responsibilities

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
Qualifications

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
What you can expect from us
  • 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.

Employment Type: FULL_TIME