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Remote Video Annotation Jobs in Phoenix, AZ (NOW HIRING)

Remote Video Annotation information

See Phoenix, AZ salary details

$37.7K

$75K

$128.1K

How much do remote video annotation jobs pay per year?

As of May 28, 2026, the average yearly pay for remote video annotation in Phoenix, AZ is $74,963.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,600.00 and $86,900.00 per year, depending on experience, location, and employer.

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

To excel as a Remote Video Annotation Specialist, you need strong attention to detail, visual accuracy, and basic computer literacy, often supported by prior experience in data labeling or related fields. Familiarity with annotation platforms (such as CVAT or Labelbox) and understanding of video formats and metadata are typically required. Effective time management, reliability, and clear communication help specialists meet deadlines and collaborate remotely. These skills ensure precise data labeling, which is crucial for training high-performing AI and machine learning models.

What are the typical daily tasks and challenges faced by a Remote Video Annotation specialist?

As a Remote Video Annotation specialist, your daily tasks typically include reviewing video footage, accurately labeling objects or actions according to specific guidelines, and ensuring data consistency for machine learning projects. One common challenge is maintaining high attention to detail over long periods, as precise annotations are crucial for training effective AI models. Additionally, you'll often collaborate with project managers or quality assurance teams to clarify requirements, discuss edge cases, and receive feedback. Flexibility and good time management are important, as workloads can vary based on project deadlines and client needs.

What is remote video annotation?

Remote video annotation is the process of labeling or tagging objects, actions, or events in video footage while working from a location outside of a traditional office, typically from home. Annotators use specialized software tools to draw boxes, create masks, or assign labels to specific frames or sequences in videos. This annotated data is essential for training and improving computer vision models used in applications like self-driving cars, security systems, and entertainment technology. Remote video annotation jobs offer flexibility, but often require attention to detail, strong computer skills, and the ability to follow detailed guidelines.

What is the difference between Remote Video Annotation vs Remote Data Labeling?

AspectRemote Video AnnotationRemote Data Labeling
Primary FocusAnnotating objects, actions, and events in videosLabeling data across various formats, including images, text, and videos
Work EnvironmentRemote, often collaborative with video review toolsRemote, using labeling platforms for different data types
Required SkillsAttention to detail, understanding of video contentAccuracy, familiarity with labeling tools

Remote Video Annotation specifically involves marking objects and actions within videos, while Remote Data Labeling covers a broader range of data types, including images and text. Both roles require attention to detail and remote work skills, but Video Annotation focuses on video content analysis, making it more specialized within the data labeling industry.

What are the most commonly searched types of Video Annotation jobs in Phoenix, AZ? The most popular types of Video Annotation jobs in Phoenix, AZ are:
What job categories do people searching Remote Video Annotation jobs in Phoenix, AZ look for? The top searched job categories for Remote Video Annotation jobs in Phoenix, AZ are:
What cities near Phoenix, AZ are hiring for Remote Video Annotation jobs? Cities near Phoenix, AZ with the most Remote Video Annotation job openings:

Egocentric Data Collection

Objectways Technologies Llc

Phoenix, AZ • Remote

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Position Summary:

We are seeking reliable individuals to participate in a paid video data collection project. Contributors will wear a comfortable head strap, attach their smartphone, or Smart Glasses(Provided by us) and record first-person (egocentric) video of normal daily activities. This data will be used to help improve next-generation AI, robotics, and computer vision systems.

What You Will Do:

Wear a head-mounted strap and securely attach your smartphone or Smart Glasses( Provided by Us)

Record 4 hours of usable first-person video per session.

Perform simple daily tasks such as walking, organizing items, cooking, shopping, working at a desk, or other routine activities.

Follow the provided capture guidelines to ensure quality.

Upload the recorded videos after each session.

Work from home:

We do not need you to work from the address we posted. You can work from home. You can collect the Smart Glasses or Mobile Phone Mounting Strap from our office in Phoenix.

Requirements:

Must be comfortable wearing a head-mounted smartphone or Smart glass for extended periods.

Ability to complete 6–8 hours of total effort to capture 4 hours of quality video.

Access to a modern smartphone with good camera quality or you can use our Smart Glasses

Must follow instructions carefully.

Reliable, self-motivated, and able to complete tasks independently.

Compensation:

You are expected to deliver us 4 hours of Usable videos. The task will take about 6 to 8 hours to collect 4 hours of Usable Videos. You will be paid $160 for 8 hours.

Bonus incentives are available for completing multiple sessions.

All equipment (head strap or Smart Glass) will be provided.

Sample Tasks:

Here are some of the tasks that we want to capture

https://objectways.com/dataset-explorer/

About Us:

Objectways is a global leader in AI data collection and annotation, supporting major technology companies in building high-quality training datasets for cutting-edge machine learning applications.

This is a remote position.