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Internship Remote Data Annotation Jobs in Marietta, GA

Internship, project, or academic experience specifically in cloud computing, analytics, or data ... Remote If you meet these qualifications and are pursuing new challenges, start your application on ...

Internship, project, or academic experience specifically in cloud computing, analytics, or data ... Remote If you meet these qualifications and are pursuing new challenges, start your application on ...

Internship, project, or academic experience specifically in cloud computing, analytics, or data ... Remote If you meet these qualifications and are pursuing new challenges, start your application on ...

Impiricus Intern

Atlanta, GA · On-site +1

$25/hr

Atlanta, GA, New York, NY, or Remote Who We Are Impiricus is the first and only AI-powered HCP ... This is a general application for our internship program - we welcome candidates interested in ...

Our trendsetting interns learn hands-on what it takes to be a staff accountant for a growing ... Some positions at Novogradac may be open to remote or hybrid work arrangements depending on ...

SAP WM CONSULTANT

Cumberland, GA · Remote

$40 - $65/hr

  • Medical

  • Vision

  • Life

  • PTO

(100% REMOTE) | CONTRACT Position Purpose The SAP WM Consultant supports the delivery, configuration ... WM processes. · Assists with data validation and coordination related to master data ...

Sr. Account Based Marketing Manager

Atlanta, GA · Remote

$100K - $130K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... non-internship marketing experience * Experience with Excel or Google Sheets (data manipulation ... Remote/hybrid flexibility * Opportunities for career growth, mentorship, and leadership * Target ...

Showing results 21-40

Internship Remote Data Annotation information

See Marietta, GA salary details

$11

$21

$39

How much do internship remote data annotation jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for internship remote data annotation in Marietta, GA is $21.33, according to ZipRecruiter salary data. Most workers in this role earn between $16.39 and $23.22 per hour, depending on experience, location, and employer.

What is a remote data annotation internship?

A remote data annotation internship is a temporary position where interns work from home or another remote location to label, categorize, or tag data such as images, text, or audio. This annotated data is often used to train machine learning models and improve artificial intelligence systems. Interns typically use specialized platforms or tools to complete their tasks, and gain hands-on experience in data handling, quality control, and understanding AI workflows. The internship is ideal for those interested in technology, data science, or AI, and often requires strong attention to detail and good communication skills.

What does a remote data annotation intern do, and how is performance evaluated?

As a remote data annotation intern, your primary tasks will involve reviewing and labeling data—such as images, text, or audio—according to specific guidelines provided by your team. You'll likely work with annotation tools, follow detailed instructions to ensure high-quality and consistent labeling, and may participate in quality assurance checks. Performance is generally evaluated based on annotation accuracy, speed, and your ability to follow instructions, with regular feedback provided via virtual meetings or project management platforms. Effective communication and attention to detail are key to succeeding in this collaborative, remote environment.

What skills and qualifications are needed to thrive as a remote data annotation intern?

To thrive as a Remote Data Annotation Intern, you need attention to detail, basic data processing skills, and familiarity with labeling guidelines, generally supported by a high school diploma or relevant coursework. Experience with annotation platforms, spreadsheets, and sometimes basic programming tools or machine learning frameworks is often required. Strong communication, time management, and the ability to follow precise instructions are valuable soft skills in this role. These skills ensure high-quality, accurate data labeling, which is critical for training reliable machine learning models.

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

AspectInternship Remote Data AnnotationData Labeling Specialist
CredentialsTypically students or entry-level with basic computer skillsRelevant experience or certifications in data annotation or related fields
Work EnvironmentRemote, flexible hours, often part-timeRemote or on-site, depending on employer, often full-time
Industry UsageCommon in AI/ML projects, tech companies, research institutionsUsed in AI/ML, autonomous vehicles, healthcare, and tech sectors

Internship Remote Data Annotation roles are usually entry-level, temporary positions aimed at gaining experience, while Data Labeling Specialists are more experienced roles focused on accurately annotating data for machine learning models. Both roles are essential in AI development but differ in experience requirements and job scope.

What are popular job titles related to Internship Remote Data Annotation jobs in Marietta, GA?

For Internship Remote Data Annotation jobs in Marietta, GA, the most frequently searched job titles are:

What job categories do people searching Internship Remote Data Annotation jobs in Marietta, GA look for?

The top searched job categories for Internship Remote Data Annotation jobs in Marietta, GA are:

What cities near Marietta, GA are hiring for Internship Remote Data Annotation jobs?

Cities near Marietta, GA with the most Internship Remote Data Annotation job openings:

Infographic showing various Internship Remote Data Annotation job openings in Marietta, GA as of August 2026, with employment types broken down into 71% Part Time, and 29% Contract. Highlights an 100% Remote job distribution, with an average salary of $44,370 per year, or $21.3 per hour.

Junior Data Engineer

Sequoia Connect

Atlanta, GA • Remote

Full-time

Posted 6 days ago


Job description

At Sequoia Connect, we are a Talent-First Technology Ecosystem that redefines how elite professionals interact with the global digital landscape. We move beyond traditional models to act as a catalyst for the top 1% of global talent, connecting human potential with complex industrial execution. By joining our inner circle, you are not simply taking a position; you are aligning with a strategic partner dedicated to updating your "Human OS" and accelerating your growth through world-class, high-impact projects.

We are currently partnering with a rapidly growing, automation-led powerhouse that serves 31 Fortune 500 companies across the financial, healthcare, and manufacturing sectors. With a global workforce of over 32,000 employees and a presence in 28 countries, our client is a titan of digital transformation. Their "Automate Everything, Cloudify Everything" strategy ensures you will be working at the absolute forefront of AI-driven automation and cloud solutions.

This is your chance to thrive in a "Customer Success, First and Always" environment that prizes continuous learning and radical ownership. You will collaborate within an international network of expertise across 39 delivery centers worldwide, gaining exposure to complex engineering challenges that redefine industrial standards. If you are a driven professional looking for a dynamic, forward-thinking workplace where your growth is the priority, this is where you belong.

We are currently searching for a Junior Data Engineer:

The Challenge (Responsibilities)

  • Assist in building and maintaining ETL pipelines using Python and PySpark.
  • Support the development of workflows utilizing AWS Glue, Lambda, and Step Functions.
  • Work extensively with cloud data storage platforms, including S3, Redshift, RDS, and Oracle.
  • Write complex SQL queries for data extraction, transformation, validation, and reporting.
  • Help implement basic monitoring, logging, and error handling for data pipelines.
  • Support the ingestion and processing of data from APIs and JSON payloads.
  • Collaborate with software engineers, data analysts, and business stakeholders to understand requirements.
  • Contribute to code management, technical documentation, and deployment support activities.

Your Profile (Requirements)

  • Degree holders for the visa application process.
  • 0 to 4 years of software development or data engineering experience across relevant cloud platforms.
  • Good knowledge of Python and SQL.
  • Solid understanding of AWS services, specifically S3, SNS/SQS, EMR, Glue, Lambda, Redshift, and Step Functions.
  • Strong grasp of ETL concepts and data processing fundamentals.
  • Familiarity with GitLab, Terraform, and the Software Development Life Cycle (SDLC) from development to production.
  • Familiarity with PySpark, AWS managed services, data engineering best practices, and code optimization.
  • High-Performance Mindset: Resilience, emotional intelligence, and a focus on agile delivery.
  • Technologist DNA: A deep understanding of the difference between "coding" and "engineering."

Desired

  • Exposure to PySpark, Athena, CloudWatch, SNS, and SQS.
  • Internship, project, or academic experience specifically in cloud computing, analytics, or data engineering.
  • Familiarity with cloud-native foundations or AI coding assistants (e.g., GitHub Copilot).

Languages

  • Advanced Oral English: For seamless collaboration with global teams.
  • Advanced Spanish.

Special Notes

  • Our Client is seeking candidates focused on foundational skill-building in a dynamic cloud environment.

Work Arrangement

We value flexibility to support your lifestyle. This position is available as:

  • Remote


If you meet these qualifications and are pursuing new challenges, start your application on our website to join an award-winning employer. Explore all our job openings | Sequoia Career’s Page: https://www.sequoia-connect.com/careers/


Keywords:
Phyton, SQL, PySpark, AWS Glue, ETL
Requirements:
  • 0-4 years of software development experience across the appropriate platform.
  • Good knowledge on Python and SQL.
  • Good understanding to AWS services such as S3, SNS/SQS, EMR, Glue, Lambda, Redshift, and Step Functions.
  • Good understanding of ETL concepts and data processing fundamentals.
  • Familiarity with GitLab/Terraform and SDLC from development to production.
  • Familiarity to PySpark, AWS managed services, data engineering best practices, and code optimization.
  • Good analytical, problem-solving, and communication skills.