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Data Annotation Jobs in Georgia (NOW HIRING)

... annotation, and symbology * Engage in storm restoration activities * Validate GIS model connectivity and correct connectivity issues * /Perform quality control and data validation activities

... annotation, and symbology * Engage in storm restoration activities * Validate GIS model connectivity and correct connectivity issues * Perform quality control and data validation activities

Posted today

... annotation, and symbology * Engage in storm restoration activities * Validate GIS model connectivity and correct connectivity issues * Perform quality control and data validation activities

... annotation, and symbology * Engage in storm restoration activities * Validate GIS model connectivity and correct connectivity issues * Perform quality control and data validation activities

... annotation, and symbology * Engage in storm restoration activities * Validate GIS model connectivity and correct connectivity issues * Perform quality control and data validation activities

Posted today

Medical Coder - Remote

Atlanta, GA · Remote

$50 - $80/hr

Familiarity with digital annotation tools or healthcare data projects is a plus. * Commitment to accuracy, quality, and continuous learning in healthcare coding and technology

Posted today

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Showing results 21-40

Data Annotation information

See Georgia salary details

$7

$19

$42

How much do data annotation jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for data annotation in Georgia is $19.63, according to ZipRecruiter salary data. Most workers in this role earn between $13.28 and $23.38 per hour, depending on experience, location, and employer.

What does a data annotation do?

A typical workday as a Data Annotator involves reviewing datasets—such as images, audio, text, or video—and accurately labeling or categorizing information according to specific project guidelines. Most Data Annotators work independently, but they often collaborate with project managers or data scientists to clarify requirements and resolve ambiguities. Tasks may be repetitive, but adhering to precise standards is vital for maintaining data quality. Work environments can range from technology companies to remote or freelance settings, and advancement opportunities exist as team leads or quality assurance specialists for those who excel in consistency and reliability.

How much money can I make doing data annotation?

Data annotation jobs typically pay between $10 and $20 per hour, depending on the complexity of the task and the employer. Experienced annotators or those working on specialized projects may earn higher rates, especially if they have skills in specific tools or domains. Earnings can vary based on whether the work is freelance, part-time, or full-time, and some platforms offer bonuses for accuracy or speed.

What is a data annotation?

A Data Annotation job involves labeling and categorizing data, such as text, images, audio, or video, to help train machine learning models. Annotators apply tags, bounding boxes, or classifications to data based on specific guidelines. This process improves the accuracy of AI systems in recognizing patterns and making predictions. Many data annotation jobs require attention to detail and familiarity with specific domains. It is commonly used in applications like autonomous driving, natural language processing, and computer vision.

What are the key skills and qualifications needed to thrive in data annotation?

To thrive in Data Annotation, you need strong attention to detail, accuracy, and basic data handling skills, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling software, or content management systems is frequently required, though specific certifications are rare. Excellent communication, time management, and the ability to focus on repetitive tasks distinguish top performers in this role. These skills are crucial because accurate and consistent data annotation directly impacts the quality of machine learning models and AI applications.

What are the most commonly searched types of Data Annotation jobs in Georgia? The most popular types of Data Annotation jobs in Georgia are:
What cities in Georgia are hiring for Data Annotation jobs? Cities in Georgia with the most Data Annotation job openings:
Infographic showing various Data Annotation job openings in Georgia as of August 2026, with employment types broken down into 63% Full Time, 9% Part Time, and 28% Contract. Highlights an 73% In-person, 5% Hybrid, and 22% Remote job distribution, with an average salary of $40,839 per year, or $19.6 per hour.

Senior Computer Vision Engineer (Egocentric), Data Foundry

Stord

Atlanta, GA

$101K - $138K/yr

Full-time

Posted 19 days ago


Stord rating

3.1

Company rating: 3.1 out of 10

Based on 7 frontline employees who took The Breakroom Quiz


Job description

Stord is The Consumer Experience Company, powering seamless checkout through delivery for today's leading brands. Stord is rapidly growing and is on track to double our revenue in the next 18 months. To meet and exceed this target, Stord is strategically scaling teams across the entire company, and seeking energetic experts to help us achieve our mission.

By combining comprehensive commerce-enablement technology with high-volume fulfillment services, Stord provides brands a platform to compete with retail giants. Stord manages over $10 billion of commerce annually through its fulfillment, warehousing, transportation, and operator-built software suite including OMS, Pre- and Post-Purchase, and WMS platforms. Stord is leveling the playing field for all brands to deliver the best consumer experience at scale.

With Stord, brands can increase cart conversion, improve unit economics, and drive sustained customer loyalty. Stord's end-to-end commerce solutions combine best-in-class omnichannel fulfillment and shipping with leading technology to ensure fast shipping, reliable delivery promises, easy access to more channels, and improved margins on every order.

Hundreds of leading DTC and B2B companies like AG1, True Classic, Native, Seed Health, quip, goodr, Sundays for Dogs, and more trust Stord to deliver industry-leading consumer experiences on every order. Stord is headquartered in Atlanta with facilities across the United States, Canada, and Europe. Stord is backed by top-tier investors including Kleiner Perkins, Franklin Templeton, Founders Fund, Strike Capital, Baillie Gifford, and Salesforce Ventures.

Build the Vision Systems Powering the Future of Physical AI.
Stord operates the largest independent e-commerce fulfillment network in the U.S. - with 20+ fulfillment centers, 4,000+ warehouse associates, and nearly 100 million packages shipped annually. We are transforming this operational infrastructure into one of the most valuable sources of training data for the next generation of physical AI.
We are building a new business line at the intersection of robotics, computer vision, and AI data - and we are looking for an experienced Computer Vision Engineer to help build the technical foundation from the ground up.
This is a hands-on builder role for a technical leader who can design, prototype, and productionize perception systems that transform real-world environments into high-quality AI training data.Why This Role:

This is a rare opportunity to build the technical foundation of a new AI business from the ground up - combining real-world operational infrastructure with cutting-edge computer vision and robotics.

You will have:

  • A structural advantage no startup can easily replicate- access to one of the largest real-world environments for collecting physical AI training data.

  • Direct exposure to the fastest-growing AI market- partnering with robotics companies, AI labs, and teams building the future of intelligent systems.

  • True technical ownership- the opportunity to define architecture, build foundational systems, and shape the future of Embodied AI data.

  • Executive partnership- working closely with Stord's CTO and Co-Founder to define strategy, accelerate execution, and remove barriers.

What You Will Own:

You will own the early computer vision and egocentric perception stack - including data capture systems, vision pipelines, model development, and the infrastructure required to deliver high-quality datasets at scale.

Working closely with a small, highly technical team, you will help define the architecture, build the systems, and establish the technical standards for Stord's Embodied AI data platform.

Build the Data Product & Capture Platform

  • Define and evolve Stord's Embodied AI data products across quality tiers - from RGB egocentric video to depth-enhanced and multimodal datasets with hand pose, body pose, and rich annotations.

  • Determine the right technical investments based on customer requirements and the needs of emerging robotics and AI models.

  • Establish data quality standards and evaluation frameworks to ensure datasets meet production-level requirements.

Build the Perception Stack

  • Design and develop perception systems including:

    • Object detection, tracking, and segmentation

    • Depth estimation and 3D reconstruction

    • 6DoF pose estimation

    • Multi-view 3D hand and body pose estimation

    • Egocentric and fixed-camera perception systems

  • Build robust solutions designed for complex, real-world environments - not just benchmark datasets.

Own the Hardware + Vision Integration

  • Design and deploy camera systems and perception rigs across warehouse environments.

  • Own camera calibration, multi-camera synchronization, epipolar geometry, and 3D reconstruction workflows.

  • Develop solutions for deriving accurate spatial understanding from multimodal sensor inputs and video data.

Build Automated Labeling & Data Pipelines

  • Develop VLM-assisted and automated annotation workflows with human-in-the-loop quality systems.

  • Integrate labeling tools and processes that improve scalability while maintaining dataset accuracy.

  • Build pipelines that transform raw video into production-ready training datasets.

Train, Optimize, and Deploy Models

  • Design, fine-tune, evaluate, and optimize computer vision and multimodal models on large-scale video datasets.

  • Build reproducible training and deployment workflows that move beyond experimentation and into production.

  • Establish evaluation methodologies that measure model performance, reliability, and quality.

What You'll Need:
  • 8+ years of experience building and shipping production computer vision or perception systems (or an MS/PhD in Computer Vision, Machine Learning, Robotics, or a related field with 6+ years of hands-on industry experience).

  • Experience building perception systems that operate on real-world, imperfect data - beyond academic benchmarks.

  • Demonstrated experience developing or scaling egocentric vision, robotics perception, autonomous systems, or AI data platforms.

  • Deep expertise in computer vision fundamentals and modern tooling, including:

    • CNNs and vision transformers

    • Object detection, segmentation, and tracking

    • Depth estimation and 3D vision

    • 2D/3D pose estimation

    • Camera calibration and geometric computer vision

  • Experience owning complex perception problems end-to-end - from data collection and model development through evaluation, optimization, and deployment.

  • Strong understanding of large-scale video and multimodal datasets, including data quality measurement and evaluation methodologies.

  • Experience taking ambiguous, 01 technical challenges and turning them into scalable systems with limited resources.

  • Ability to influence technical direction, establish engineering standards, and mentor other engineers.

  • Expert-level Python skills and strong software engineering fundamentals; C++ experience where performance requirements demand it.


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