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Full Time Annotation Jobs (NOW HIRING)

Propio Language Services

AI Engineer

Leawood, KS · On-site

$111.40K - $133.80K/yr

Job Type Full-time Description Propio Language Services is a provider of the highest quality ... The ideal candidate can build scalable data pipelines, design high-quality annotation and QA ...

Boston College

Manager, UCC Digest

Chestnut Hill, MA · On-site

Ranked 37 among national universities, Boston College has 923 full-time and 1,336 FTE faculty, 2 ... If necessary, restructure and rewrite the annotation to ensure its professional quality for the ...

Welocalize, Inc.

OR

$16 - $20.75/hr

Data Management and Annotation: * Design and develop test and training datasets as per the criteria provided by the project manager and other full-time employees. * Handle data efficiently, ensuring ...

Welocalize, Inc.

Data Quality Analyst

New York, NY

Data Management and Annotation: * Design and develop test and training datasets as per the criteria provided by the project manager and other full-time employees. * Handle data efficiently, ensuring ...

Figure

Data Quality Manager

San Jose, CA · On-site

$140K - $200K/yr

Partner with engineering to design and develop new internal tooling for annotation, QA, and data ... for this full-time position is between $140,000 - $200,000 annually. The pay offered for this ...

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Full Time Annotation information

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How much do full time annotation jobs pay per year?

As of May 30, 2026, the average yearly pay for full time annotation in the United States is $75,506.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,500.00 and $88,500.00 per year, depending on experience, location, and employer.

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

To excel as a Full Time Annotation Specialist, you need keen attention to detail, strong analytical skills, and a solid understanding of data labeling concepts, often supported by a relevant degree or prior experience in data-related roles. Familiarity with annotation platforms, data management tools, and sometimes scripting languages like Python is commonly required. Strong communication, time management, and the ability to focus on repetitive tasks help individuals stand out in this position. These skills are essential to ensure high-quality, accurate data annotations that directly impact the performance of AI and machine learning models.

What are some common challenges faced in a full-time annotation role, and how can they be addressed?

Full-time annotation professionals often encounter challenges such as maintaining consistency and accuracy across large datasets, managing repetitive tasks, and meeting tight deadlines. These challenges can be addressed by developing a strong attention to detail, regularly cross-checking work, and utilizing annotation guidelines provided by the employer. Additionally, collaborating with team members and participating in quality assurance reviews helps ensure high standards and reduces errors. Many organizations offer training and feedback sessions to support continuous improvement and professional growth in this role.

What is a Full Time Annotation job?

A Full Time Annotation job involves labeling and categorizing data, such as images, text, audio, or video, to help train machine learning models. Annotators carefully tag or highlight specific information in datasets, following detailed guidelines to ensure accuracy. This role is essential in industries like artificial intelligence, self-driving cars, and natural language processing, where high-quality labeled data is crucial for model performance. Full Time Annotation positions typically require attention to detail, consistency, and sometimes familiarity with specialized tools or subject matter.

What is the difference between Full Time Annotation vs Part Time Annotation?

AspectFull Time AnnotationPart Time Annotation
Work HoursTypically 40 hours/weekFewer hours, flexible schedule
CredentialsBasic training, attention to detailSame as full time, often same requirements
Work EnvironmentOffice or remote, consistent scheduleFlexible, part-time settings
Employer UsageFull-time positions in tech companies, AI firmsPart-time roles, freelance or contract basis

Full Time Annotation involves working a standard full-time schedule with consistent hours, often in a dedicated work environment, suitable for those seeking stable employment. Part Time Annotation offers flexible hours, ideal for individuals balancing other commitments or seeking supplemental income. Both roles require similar skills and training but differ mainly in hours and employment structure.

More about Full Time Annotation jobs
What cities are hiring for Full Time Annotation jobs? Cities with the most Full Time Annotation job openings:
What are the most commonly searched types of Annotation jobs? The most popular types of Annotation jobs are:
What states have the most Full Time Annotation jobs? States with the most job openings for Full Time Annotation jobs include:
What job categories do people searching Full Time Annotation jobs look for? The top searched job categories for Full Time Annotation jobs are:
Full Time Annotation jobs near you

Vision-Language-Action (VLA) Annotator

Objectways Technologies Llc

Phoenix, AZ

$25/hr

Full-time

Posted 26 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.