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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 22, 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 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 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 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 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 August 2026, with employment types broken down into 77% Full Time, 18% Part Time, 1% Temporary, and 4% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $77,209 per year, or $37.1 per hour.

Senior Computer Vision Engineer (Egocentric), Data Foundry Software

Front Door Defense

Atlanta, GA • On-site

$160 - $230/hr

Other

Posted 7 days ago


Job description

Senior Computer Vision Engineer (Egocentric), Data Foundry Build and scale an egocentric perception stack from data collection to production deployment

Location: Atlanta, Georgia

About The Role Computer Vision Engineer And Technologist

Stord operates the largest independent e-commerce fulfillment network in the US — 20+ fulfillment centers, 4,000+ warehouse associates, and nearly 100 million packages shipped annually. We are building a new business line that turns this operational infrastructure into some of the most valuable training data assets in physical AI. We are looking for an experienced computer vision engineer and technologist to build and scale this business from the ground up.

What You Will Own

You will own the early egocentric video stack — data collection, vision models and pipelines, and rigs. You'll partner closely with a small team to operationalize. This is a builder-operator role. You will:

  • Define and deliver the product. You will own the data product across quality tiers — from RGB egocentric video through depth-enhanced and full multimodal capture with hand pose and annotations. You will decide what gets built, in what order, based on what buyers will actually pay for. You will hold the line on quality.
  • Run the capture and delivery program. You will stand up the warehouse capture operation: camera and rig hardware selection, enrollment, edge processing, and the processing pipelines that package datasets for delivery. You will coordinate across warehouse operations, engineering, and customers to ship datasets on spec and on schedule.
  • Build the perception stack. Detection, tracking, and segmentation, plus depth/3D reconstruction and 6DoF, multi-view 3D hand/body pose estimation from egocentric and fixed-camera capture.
  • Stand up VLM-assisted and automated labeling with human-in-the-loop QA to drive down cost per annotated hour, and integrate the annotation tooling.
  • Own the hardware vision intersection. Camera calibration, epipolar/multi-view geometry, and frame-accurate time-sync across multi-camera and egocentric rigs; derive 3D pose by triangulation where no direct sensor exists.
  • Train and ship models. Design, fine-tune, and optimize CV/multimodal models on large unstructured video datasets, and get them reproducible and production-ready, not stuck in a notebook.
What You Bring
  • Experiencing standing up and scaling an egocentric perception stack. You have built and run a similar product end to end at a robotics or AI data company. You have driven the full lifecycle: hardware setup, embedded perception, data pipelines, ensuring quality, and delivering it to production teams who depend on it.
  • 8+ years building and shipping production computer-vision/perception systems (or an MS/PhD in CV, ML, or robotics plus 6+ years hands-on), including systems that ran on messy real-world data, not just benchmarks.
  • Deep expertise in computer vision and tooling — track record of leveraging existing tooling and designing, training, and debugging CNNs and vision transformers from scratch.
  • Strong command of geometric computer vision: camera calibration, depth estimation, and 2D/3D pose estimation
  • End-to-end ownership of a major perception problem: from data and model design through evaluation, optimization, and deployment, with measurable accuracy and reliability outcomes.
  • Track record of setting technical direction for a team or large workstream and raising the bar for other engineers.
  • Proven ability to take ambiguous, 0→1 problems with no established playbook and drive them to a working system with limited resources.
  • Experience with large unstructured datasets (video/multimodal) and the eval discipline to instrument accuracy rather than eyeball it.
  • Expert Python and strong software-engineering fundamentals; C++ where performance demands it.
Why This Role

This is a rare opportunity to build a high-growth business from the ground-up with infrastructure and resources to support. You will have:

  • A structural moat that no startup can replicate
  • Direct access to the fastest-growing buyer market in AI
  • CTO/Co-Founder as your direct partner.
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