1

Temporary Ai Data Annotation Jobs in Georgia (NOW HIRING)

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

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

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 ...

New

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 ...

New

Support data annotation and quality validation activities * Maintain accurate operational records ... intelligence (AI) tools to support parts of the hiring process, such as reviewing applications ...

Support data annotation and quality validation activities * Maintain accurate operational records ... intelligence (AI) tools to support parts of the hiring process, such as reviewing applications ...

$171K - $321K/yr

AI is the primary builder of the Fabric, not merely its consumer. This leader deploys agents that ... annotation at enterprise scale. Responsible for * Certified, versioned data products and semantic ...

Data annotation and quality review * Exploratory data analysis and model fail state analysis ... We use the latest in AI/ML technology to help our customers break new ground at scale. We are a ...

next page

Showing results 1-20

Temporary Ai Data Annotation information

What is a temporary AI data annotation job?

Temporary AI Data Annotation jobs involve labeling, categorizing, or tagging data such as images, text, audio, or video for the purpose of training artificial intelligence (AI) and machine learning models. These roles are often short-term or contract positions, as they are needed for specific projects or during certain stages of data processing. Annotators play a critical role in ensuring the quality and accuracy of datasets, which directly impacts the performance of AI systems. No advanced technical skills are usually required, but attention to detail and consistency are important. These jobs may be offered remotely or on-site, depending on the employer.

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

AspectTemporary Ai Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic skills, sometimes specific software knowledge
Work EnvironmentRemote or on-site, project-basedRemote or on-site, often similar settings
Industry UsageAI, machine learning, tech companiesAI, autonomous vehicles, tech sectors
Job FocusAnnotating data for AI trainingLabeling data for machine learning models

Temporary Ai Data Annotation involves short-term projects focused on preparing data for AI systems, while Data Labeler is a broader role that includes labeling various data types for machine learning. Both roles require similar skills and are used in tech industries, but Temporary Ai Data Annotation emphasizes project-based work specifically for AI training datasets.

What are the key skills and qualifications needed to thrive as a temporary AI data annotation specialist, and why are they important?

To thrive as a Temporary AI Data Annotation Specialist, you need keen attention to detail, strong analytical skills, and the ability to follow complex guidelines, often supported by a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools like Labelbox or Prodigy, and basic computer literacy are typically required. Reliability, consistency, and the ability to work independently stand out as valuable soft skills in this role. These competencies are essential for producing high-quality, accurate data that directly impacts the effectiveness of machine learning models.

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

One of the main challenges in a Temporary AI Data Annotation position is maintaining consistent accuracy and attention to detail, especially when working with large volumes of data. Annotation guidelines can be complex and may change depending on project requirements, so adaptability and clear communication with the team are key. Managing repetitive tasks while ensuring high-quality work can be demanding, but using productivity tools and taking regular breaks can help maintain focus. Collaborating with quality assurance leads and participating in feedback sessions are also important for continuous improvement.

What are the most commonly searched types of Ai Data Annotation jobs in Georgia?

The most popular types of Ai Data Annotation jobs in Georgia are:

What are popular job titles related to Temporary Ai Data Annotation jobs in Georgia?

For Temporary Ai Data Annotation jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Temporary Ai Data Annotation jobs in Georgia look for?

The top searched job categories for Temporary Ai Data Annotation jobs in Georgia are:

What cities in Georgia are hiring for Temporary Ai Data Annotation jobs?

Cities in Georgia with the most Temporary Ai Data Annotation job openings:

Infographic showing various Temporary Ai Data Annotation job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, 1% Temporary, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

AI Data Scientist Expert - Remote

YO AI Labs

Atlanta, GA • Remote

$100 - $200/hr

Part-time

Posted 2 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.