1

Annotation Labelling Jobs in Virginia (NOW HIRING)

Review, label, and categorize images to support machine learning and AI model training. * Follow detailed annotation and redaction standards to ensure consistency. * Conduct quality checks to ...

Review, label, and categorize images to support machine learning and AI model training. * Follow detailed annotation and redaction standards to ensure consistency. * Conduct quality checks to ...

Annotation Labelling information

What is annotation labelling?

Annotation labelling is the process of tagging or marking data—such as images, text, or audio—with relevant information or labels. This is an essential step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms understand and learn from raw data. Annotation labelling can include tasks like identifying objects in photos, transcribing speech, or categorizing text. Skilled annotators ensure accuracy and consistency to improve model performance. People in this role often use specialized tools or software to streamline and standardize the annotation process.

What are the key skills and qualifications needed to thrive as an Annotation Labelling Specialist, and why are they important?

To thrive as an Annotation Labelling Specialist, you need strong attention to detail, data analysis capabilities, and familiarity with data annotation standards, usually supported by a background in computer science or related fields. Proficiency with annotation tools such as Labelbox, CVAT, or Supervisely, and sometimes knowledge of basic programming or scripting, is typically required. Excellent communication, consistency, and the ability to follow complex instructions are crucial soft skills for producing high-quality labeled data. These skills ensure the accuracy and reliability of datasets, which are foundational for successful machine learning and AI model development.

What are some common challenges faced by Annotation Labelling professionals, and how can they be managed?

Annotation Labelling professionals often encounter challenges such as maintaining high accuracy while handling repetitive data, meeting tight deadlines, and adapting to evolving project guidelines. To manage these, it’s important to develop strong attention to detail, regularly communicate with team leads to clarify instructions, and leverage annotation tools efficiently. Collaborating closely with quality assurance teams can also help identify and correct errors early, ensuring consistently high-quality outputs.

What is the difference between Annotation Labelling vs Data Labeling Specialist?

AspectAnnotation LabellingData Labeling Specialist
CredentialsBasic technical skills, attention to detailSimilar skills, sometimes additional domain knowledge
Work EnvironmentData annotation platforms, remote or officeData annotation tasks, often remote or in-office
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, healthcare, retail
Search & ComparisonCommonly compared for entry-level data tasksRelated but broader role

Annotation Labelling involves marking data such as images, text, or videos to train AI models. Data Labeling Specialists perform similar tasks but may have a broader scope, including verifying and managing labeled data. Both roles are essential in AI development, often overlapping in skills and work environment, but Annotation Labelling is more focused on the annotation process itself.

What are popular job titles related to Annotation Labelling jobs in Virginia? For Annotation Labelling jobs in Virginia, the most frequently searched job titles are:
What cities in Virginia are hiring for Annotation Labelling jobs? Cities in Virginia with the most Annotation Labelling job openings:
Data Annotation Specialist

Data Annotation Specialist

CaseGuard

Arlington, VA

$40K - $50K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 5 days ago


Job description

We are seeking a detail-oriented Data Entry to support data preparation initiatives. This role is responsible for redacting sensitive information from files and reviewing, labeling, and categorizing images to support machine learning model training. Accuracy, confidentiality, and consistency are critical to success in this role.

Key Responsibilities:

  • Review digital documents and redact sensitive or confidential information according to established guidelines.
  • Perform accurate data entry and data validation to ensure high-quality datasets.
  • Review, label, and categorize images to support machine learning and AI model training.
  • Follow detailed annotation and redaction standards to ensure consistency.
  • Conduct quality checks to identify errors or inconsistencies.
  • Handle sensitive data with discretion and comply with privacy and security policies.
  • Meet productivity and accuracy benchmarks while managing multiple tasks.

Qualifications:

  • Bachelor's degree in any field.
  • High attention to detail and ability to work with repetitive tasks while maintaining accuracy.
  • Basic technical proficiency and ability to learn new software tools quickly.
  • Strong organizational skills and ability to meet deadlines.
  • Excellent communication skills and ability to follow instructions.
  • Ability to maintain confidentiality and handle sensitive information.

Benefits:

  • Competitive Salary
  • Stock Option
  • Medical, Dental, and Vision Insurance
  • 401K
  • Paid Vacation
  • Ten paid holidays per year
  • Friendly and Learning environment

Salary Range: $40,000 - $50,000

About CaseGuard

CaseGuard is a software company that helps law enforcement agencies, federal agencies, hospitals, schools, airports, and others manage all their media redaction needs in one easy-to-use redaction software. CaseGuard Studio is one of its kind. Our team is driven by a passion for great software design, the creation of great products, and the creative process, CaseGuard implements innovative ideas across multiple services and agencies.