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Hourly Ai Data Annotation Jobs in Silver Spring, MD

YO AI Labs

AI Data Science Expert - Remote

Washington, DC · Remote

$100 - $200/hr

Job Title: AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job ... Data Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving

New

CaseGuard

Data Annotation Specialist

Arlington, VA · On-site

$40K - $50K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Review, label, and categorize images to support machine learning and AI model training. * Follow ... Handle sensitive data with discretion and comply with privacy and security policies. * Meet ...

CaseGuard

Data Annotation Specialist

Arlington, VA

$40K - $50K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Review, label, and categorize images to support machine learning and AI model training. * Follow ... Handle sensitive data with discretion and comply with privacy and security policies. * Meet ...

YO AI Labs

AI Finance Expert - Remote

Washington, DC · Remote

$100 - $200/hr

AI Finance Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job Overview We are ... Data Annotation * Problem-Solving * Independent Research * Attention to Detail Preferred ...

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Innodata Inc.

AI Solutions Engineer

Washington, DC

$75 - $80/hr

... annotation experience * DataCard or ML data provenance framework familiarity The expected hourly ... The AI Solutions Engineer operates at the AI/ML configuration and integration layer above the ...

YO AI Labs

AI Consulting Expert - Remote

Washington, DC · Remote

$100 - $200/hr

Job Title: AI Consulting Domain Remote Job Type: Contractor (Part-Time) Location: Remote Job ... Data Annotation * Fact Checking * Independent Research * Problem-Solving * Attention to Detail ...

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Hourly Ai Data Annotation information

What is an hourly AI data annotation?

An Hourly AI Data Annotation job involves labeling, tagging, or categorizing data—such as images, text, or audio—to help train machine learning models. Annotators follow specific guidelines to ensure that the data is accurately labeled so that AI systems can learn to recognize patterns and make decisions. These jobs are typically paid by the hour and may require attention to detail, consistency, and sometimes familiarity with specialized annotation tools. This work is essential for improving the accuracy and usefulness of artificial intelligence applications.

What are some common challenges faced by hourly AI data annotators, and how can they be managed?

Hourly AI data annotators often encounter challenges such as repetitive tasks, maintaining high accuracy under time constraints, and adapting to evolving project guidelines. To manage these, it's important to take regular breaks to avoid fatigue, stay up to date with training materials, and communicate proactively with team leads if instructions are unclear. Many teams use collaborative tools and regular feedback sessions to support annotators and ensure consistent quality, making teamwork and attention to detail vital for success in this role.

What are the key skills and qualifications needed to thrive as an hourly AI data annotator?

To thrive as an AI Data Annotator, you need strong attention to detail, accuracy, and a basic understanding of data labeling concepts, typically supported by a high school diploma or equivalent. Familiarity with annotation tools such as Labelbox or Supervisely, and basic computer proficiency, are often required. Critical thinking, consistency, and effective communication are valuable soft skills in this role. These skills ensure high-quality, reliable data that directly improves the performance of AI and machine learning models.

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

AspectHourly Ai Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or in-office, flexible hoursRemote or in-office, flexible hours
Industry UsageAI, machine learning, tech companiesAI, machine learning, tech companies
Job FocusAnnotating data for AI training, often with specific instructionsLabeling data to help AI models learn, often similar tasks

Hourly Ai Data Annotation and Data Labeler roles are similar, focusing on preparing data for AI systems. The main difference lies in terminology; 'Hourly Ai Data Annotation' emphasizes the paid hourly aspect and the specific task of annotating data for AI training, while 'Data Labeler' is a broader term used interchangeably in the industry. Both roles require similar skills and are used in the same industry sectors.

What are the most commonly searched types of Ai Data Annotation jobs in Silver Spring, MD?

The most popular types of Ai Data Annotation jobs in Silver Spring, MD are:

What are popular job titles related to Hourly Ai Data Annotation jobs in Silver Spring, MD?

For Hourly Ai Data Annotation jobs in Silver Spring, MD, the most frequently searched job titles are:

What job categories do people searching Hourly Ai Data Annotation jobs in Silver Spring, MD look for?

The top searched job categories for Hourly Ai Data Annotation jobs in Silver Spring, MD are:

What cities near Silver Spring, MD are hiring for Hourly Ai Data Annotation jobs?

Cities near Silver Spring, MD with the most Hourly Ai Data Annotation job openings:

Hourly Ai Data Annotation jobs near you
Infographic showing various Hourly Ai Data Annotation job openings in Silver Spring, MD as of August 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 67% In-person, and 33% Remote job distribution.

AI Data Scientist Expert - Remote

YO AI Labs

Washington, DC • Remote

$100 - $200/hr

Part-time

Posted 3 days ago

New

Job description

Job Title: AI Data Science Domain Expert

Job Type: Contractor (Part-Time)
Location: Remote

Job Overview

We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative project focused on advancing next-generation AI systems. In this role, you will review, evaluate, and refine AI-generated technical and analytical content to improve model accuracy, reasoning, and overall performance. No prior AI experience is required—your data science expertise, analytical thinking, and communication skills are what matter most.

Key Responsibilities
  • Review, edit, and refine AI-generated content for accuracy, clarity, and technical relevance.
  • Develop, optimize, and evaluate prompts to improve AI model performance.
  • Conduct rubric-based assessments of AI outputs and provide structured feedback.
  • Perform independent research and fact-checking to validate technical information.
  • Annotate data and support quality assurance initiatives for AI training.
  • Interpret complex datasets and prepare clear technical reports and summaries.
  • Collaborate remotely with project teams to improve AI models and workflows.
Required Skills
  • Critical Thinking
  • Analytical Reasoning
  • Prompt Engineering
  • AI Output Evaluation
  • Quality Assurance
  • Technical Documentation
  • Technical & Report Writing
  • Content Review & Editing
  • Data Annotation
  • Data Interpretation
  • Fact Checking
  • Independent Research
  • Problem-Solving
  • Attention to Detail
Preferred Qualifications
  • 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.
  • Experience producing or reviewing research papers, analytical reports, technical documentation, experiment summaries, or data-driven recommendations.
  • Strong analytical reasoning, critical thinking, and written communication skills.
  • Experience with data annotation, content review, or rubric-based evaluation is preferred.
  • Familiarity with prompt engineering, AI output evaluation, fact-checking, or RLHF is a plus.
  • Master's, MBA, PhD, or other advanced degree is preferred.