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3D Annotation Job Jobs (NOW HIRING)

Skild AI

Computer Vision AI & ML Engineer

San Mateo, CA · On-site

$127K - $149K/yr

Knowledge of 3D geometry, sensor processing, or multi-sensor fusion (RGB-D, LiDAR, stereo). * Experience with data annotation tools, dataset management, and augmentation techniques. * Familiarity ...

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3D Annotation Job information

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How much do 3d annotation job jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for 3d annotation job in the United States is $15.99, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $17.31 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a 3D Annotation Specialist, and why are they important?

To thrive as a 3D Annotation Specialist, you need a keen eye for detail, spatial awareness, and basic computer skills, often supported by a background in computer graphics, engineering, or related fields. Familiarity with 3D annotation tools such as Labelbox, Supervisely, or CVAT, and experience with file formats like OBJ or PLY are typically required. Strong problem-solving abilities, patience, and effective communication skills help ensure accuracy and collaboration within annotation teams. These skills are crucial for producing high-quality labeled data, which directly impacts the effectiveness of AI and machine learning models relying on 3D spatial information.

What are 3D annotation jobs?

3D annotation jobs involve labeling or tagging objects within three-dimensional data, such as point clouds, 3D models, or volumetric images. These annotations are crucial for training artificial intelligence and machine learning models, especially in fields like autonomous vehicles, robotics, and augmented reality. Workers typically use specialized software tools to mark objects, define boundaries, or classify items in 3D space. The accuracy and quality of 3D annotations directly impact the performance of AI systems that rely on this data.

What is the difference between 3D Annotation Job vs 3D Labeling Specialist?

Aspect3D Annotation Job3D Labeling Specialist
CredentialsBasic computer skills, attention to detailSimilar credentials, often with experience in annotation tools
Work EnvironmentRemote or office-based, using annotation softwareSimilar, often in tech or AI companies
Industry UsageAutonomous vehicles, robotics, AI trainingAutonomous vehicles, AI datasets, machine learning

Both roles involve working with 3D data to prepare datasets for AI models. The main difference lies in terminology; '3D Annotation Job' is a general description of the task, while '3D Labeling Specialist' often refers to a more specialized or professional role within the same field. Both require similar skills and are used interchangeably in many companies.

What are some common challenges faced in a 3D annotation role, and how can they be addressed?

One common challenge in a 3D annotation role is ensuring high accuracy and consistency when labeling complex objects or scenes, especially in dynamic environments like autonomous driving datasets. This requires a keen eye for detail and a solid understanding of the annotation tools and guidelines. Collaborating effectively with quality assurance teams and staying updated on the latest annotation standards can help address these challenges. Additionally, regular feedback sessions and ongoing training can improve both speed and precision over time.
More about 3D Annotation Job jobs
What job categories do people searching 3D Annotation Job jobs look for? The top searched job categories for 3D Annotation Job jobs are:
3D Annotation Job jobs near you
Infographic showing various 3D Annotation Job job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, and 3% Contract. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $33,254 per year, or $16 per hour.

Vision-Language-Action (VLA) Annotator

Objectways Technologies Llc

Phoenix, AZ • Remote

$25/hr

Full-time

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

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.