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

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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 Jul 13, 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 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 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 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 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 are popular job titles related to Remote Video Annotation jobs in Phoenix, AZ? For Remote Video Annotation jobs in Phoenix, AZ, the most frequently searched job titles 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:
Remote Video Annotation jobs near you

Vision-Language-Action (VLA) Annotator

Objectways Technologies Llc

Phoenix, AZ • Remote

$25/hr

Full-time

Posted 11 days ago

Job description

Location:RemoteEmployment Type: Full-Time | 40 hours/week Compensation: $25/hour
About the Role:
We are looking for a detail-oriented and technically capable Vision-Language-Action (VLA) Annotator to join our data operations team in Phoenix, Arizona. In this role, you will be responsible for reviewing, labeling, and quality-checking multimodal datasets used to train and evaluate autonomous driving and robotics models. Your work directly impacts the safety and performance of AI systems operating in the real world.
This is a full-time, 40-hour-per-week position requiring sustained focus, sound judgment, and the ability to apply structured annotation guidelines to complex, real-world scenarios including frequent edge cases.
Key Responsibilities:
  • Review and annotate video footage, sensor telemetry, and camera feeds from autonomous vehicle test drives and robotics platforms.
  • Assess vehicle and robotic behavior in 3D space using 2D camera inputs, including approach angles, following distances, trail alignment, and controlled stop quality.
  • Use time-series telemetry data including speed, throttle, steering, and braking charts to make precise trim and segmentation decisions on data clips.
  • Apply annotation guidelines consistently while exercising independent judgment on ambiguous or edge-case scenarios.
  • Identify and flag unsafe, incomplete, or anomalous driving behaviors (e.g., rolling stops, improper following distance, out-of-distribution maneuvers).
  • Maintain high throughput and accuracy standards; participate in regular quality audits and calibration sessions.
  • Work within annotation platforms (e.g., Encord, CVAT, Label Studio, or similar) to complete labeling tasks efficiently.
  • Document and communicate recurring issues or ambiguities in the data to improve pipeline quality.
Preferred Qualifications:
  • Education: Bachelor's degree with a STEM background preferred (Engineering, Computer Science, Physics, Mathematics, GIS, or related field).
  • Spatial & Mechanical Reasoning: Demonstrated ability to interpret vehicle or robotic behavior in 3D space from 2D camera feeds. Backgrounds in robotics, automotive engineering, mechanical engineering, GIS, or simulation are strong indicators.
  • Time-Series Data Literacy: Experience reading and interpreting sensor data, telemetry charts, lab instrumentation output, or signal processing data. Comfort with chart-heavy analytical workflows is essential for making precise trim decisions.
  • Driving Familiarity: Regular driving experience, ideally in varied or off-road conditions. Must be able to distinguish safe from unsafe driving behavior, recognize complete vs. rolling stops, and assess reasonable following distances.
  • Detail Orientation with Tolerance for Ambiguity: Ability to follow precise, rule-based guidelines while also applying sound judgment on frequent edge cases. Prior experience in QA, data annotation, or lab/research settings is a strong signal.
  • Video Review Endurance: Comfort with sustained video review tasks. Prior experience in video editing, surveillance monitoring, sports performance analysis, or media production is a plus.
Nice-To-Haves:
  • Prior annotation or data labeling experience, especially in autonomy or robotics datasets.
  • Familiarity with geospatial tools, map interfaces, or GIS platforms.
  • Hands-on experience with Encord, Label Studio, CVAT, Scale AI, or comparable labeling platforms.
  • Background in autonomous vehicles, ADAS systems, or driver safety analysis.

This is a remote position.