1

Senior Video Annotation Jobs in Atlanta, GA (NOW HIRING)

Senior Video Annotation information

See Atlanta, GA salary details

$24K

$77.2K

$157.2K

How much do senior video annotation jobs pay per year?

As of Aug 1, 2026, the average yearly pay for senior video annotation in Atlanta, GA is $77,209.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,900.00 and $99,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Senior Video Annotation Specialist, and why are they important?

To excel as a Senior Video Annotation Specialist, you need advanced skills in data labeling, attention to detail, and experience with video annotation tools, often supported by a degree in computer science or a related field. Familiarity with annotation platforms like CVAT, Labelbox, or VGG Image Annotator, and understanding of basic machine learning concepts, are typically required. Strong organizational skills, problem-solving abilities, and effective communication help ensure accuracy and seamless collaboration with data science teams. These competencies are vital for producing high-quality annotated datasets that drive the performance of computer vision models.

What skills do you need for video annotation?

Senior Video Annotation roles require strong attention to detail, good visual perception, and the ability to accurately identify and label objects, actions, and scenes in videos. Familiarity with annotation tools and basic understanding of video formats and data management are also important. Additionally, skills in time management and the ability to work efficiently under deadlines are valuable.

Is video annotation hard?

Video annotation as a senior role involves attention to detail and understanding of annotation tools, which can require training and practice. The difficulty depends on the complexity of the project and the precision needed, but it generally involves repetitive tasks that demand focus and accuracy. Familiarity with software and clear guidelines can help streamline the process.

What are some common challenges faced by Senior Video Annotation professionals, and how can they be addressed?

Senior Video Annotation professionals often encounter challenges such as maintaining consistency in labeling complex visual data, meeting tight project deadlines, and managing large volumes of video content. To address these issues, it's important to establish clear annotation guidelines, utilize efficient annotation tools, and foster open communication within the annotation team. Regular training and quality assurance checks can also help ensure high accuracy and efficiency, positioning team members for leadership and quality control roles as they advance.

What does a video annotator do?

A video annotator is responsible for labeling and tagging objects, actions, and other relevant features within video footage to help train machine learning models. They use specialized tools to ensure accurate and consistent annotations, often working with guidelines and quality standards. This role requires attention to detail and familiarity with annotation software or platforms.

What is a Senior Video Annotation?

A Senior Video Annotation specialist is a professional responsible for labeling, tagging, and categorizing objects or actions within video data, often for use in machine learning and artificial intelligence projects. They oversee and guide annotation teams, ensure high-quality data labeling, and help develop guidelines and best practices. Their expertise is crucial for training accurate computer vision models, as they provide the ground truth data that algorithms learn from.

What is the highest salary for data annotator?

The highest salaries for senior video annotation roles can reach up to $70,000 to $90,000 annually, depending on experience, location, and the complexity of annotation tasks. Advanced skills in tools like CVAT or Labelbox and certifications can contribute to higher compensation in this field.

What is the difference between Senior Video Annotation vs Video Labeler?

AspectSenior Video AnnotationVideo Labeler
Required CredentialsTypically requires experience in annotation tools, basic understanding of video content, and sometimes a degree in related fieldsUsually requires familiarity with labeling software and basic video content understanding, but less experience needed
Work EnvironmentOften part of a team working on complex projects, possibly remote or in-officeTypically focused on individual tasks, often remote, with repetitive labeling work
Employer & Industry UsageUsed in AI/ML companies, autonomous vehicle development, and tech firmsCommon in data annotation companies, AI startups, and research labs

Senior Video Annotation roles involve more complex tasks, oversight, and experience, while Video Labelers focus on basic labeling tasks. The senior role often requires a deeper understanding of video content and annotation tools, making it suitable for those with more experience. Both roles are essential in AI data preparation but differ in scope and responsibility.

What are the most commonly searched types of Video Annotation jobs in Atlanta, GA? The most popular types of Video Annotation jobs in Atlanta, GA are:
What job categories do people searching Senior Video Annotation jobs in Atlanta, GA look for? The top searched job categories for Senior Video Annotation jobs in Atlanta, GA are:
Infographic showing various Senior Video Annotation job openings in Atlanta, GA as of July 2026, with employment types broken down into 1% Locum Tenens, 46% Full Time, 39% Part Time, 3% Contract, 10% Nights, and 1% Summer. Highlights an 56% Physical, 1% Hybrid, and 43% Remote job distribution, with an average salary of $77,209 per year, or $37.1 per hour.

Senior Computer Vision Engineer (Egocentric), Data Foundry

Stord

Atlanta, GA

$101K - $138K/yr

Full-time

Posted 8 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.


What Stord employees say

Pay

Hours and flexibility

Workplace

Get the full story on Breakroom