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Temporary Video Annotation Jobs (NOW HIRING)

Computer Vision Engineer

Palo Alto, CA ยท On-site

$131K - $154K/yr

Computer Vision Engineer - Data Labeling & Annotation Type: Temporary Duration: 6 months - 12 ... Annotate images and video for object detection (bounding boxes), segmentation (polygons/masks), and ...

Computer Vision Engineer

Palo Alto, CA ยท On-site

$131K - $154K/yr

Computer Vision Engineer - Data Labeling & Annotation Type: Temporary Duration: 6 months - 12 ... Annotate images and video for object detection (bounding boxes), segmentation (polygons/masks), and ...

... annotation methodsand data types including text, video, images,speechandmixed media ... Evaluate, hire, train and supervise a fluctuating staff of part-time, temporary annotators ...

Sigma is a leading global technology company specializing in data collection and annotation for ... video, images, sentences, or words. All tasks are remote , performed through an online platform ...

Sigma is a leading global technology company specializing in data collection and annotation for ... video, images, sentences, or words. All tasks are remote , performed through an online platform ...

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Temporary Video Annotation information

See salary details

$26K

$59.8K

$95K

How much do temporary video annotation jobs pay per year?

As of Jun 19, 2026, the average yearly pay for temporary video annotation in the United States is $59,788.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,000.00 and $69,500.00 per year, depending on experience, location, and employer.

What is the difference between Temporary Video Annotation vs Data Labeling Specialist?

AspectTemporary Video AnnotationData Labeling Specialist
CredentialsBasic computer skills, training in annotation toolsSimilar; often requires training in labeling software
Work EnvironmentRemote or on-site, project-basedRemote or on-site, focused on data preparation
Industry UsageAI, autonomous vehicles, surveillanceMachine learning, AI, data science
Search & Comparison IntentUnderstanding temporary annotation rolesUnderstanding data labeling roles

Temporary Video Annotation involves short-term tasks focused on labeling specific video segments for AI training, often requiring quick turnaround. Data Labeling Specialists may handle various data types, including images and text, with a broader scope. Both roles require similar skills and are used in AI and machine learning industries, but Temporary Video Annotation is more specialized for video content and temporary projects.

More about Temporary Video Annotation jobs
What cities are hiring for Temporary Video Annotation jobs? Cities with the most Temporary Video Annotation job openings:
What are the most commonly searched types of Video Annotation jobs? The most popular types of Video Annotation jobs are:
What states have the most Temporary Video Annotation jobs? States with the most job openings for Temporary Video Annotation jobs include:
Computer Vision Engineer

Computer Vision Engineer

BrightAI Corporation

Palo Alto, CA โ€ข On-site

$131K - $154K/yr

Full-time

Posted 29 days ago


Job description

Computer Vision Engineer - Data Labeling & Annotation
Type: Temporary
Duration: 6 months - 12 months
What You'll Gain
  • Exposure to the full CV pipeline, from raw data to deployed model
  • Mentorship from CV engineers working on production systems
  • Hands-on experience with YOLO, PyTorch, and modern annotation workflows
  • Concrete portfolio work - datasets, scripts, and model contributions - that translates directly to future ML/CV roles

What You'll Do
  • Annotate images and video for object detection (bounding boxes), segmentation (polygons/masks), and classification
  • Help refine labeling schemas and class taxonomies as edge cases come up
  • Write Python scripts to convert between annotation formats, validate label integrity, and generate dataset statistics
  • QA labels and surface systematic errors or ambiguous cases
  • Run baseline YOLO training experiments to evaluate dataset quality and identify labeling gaps
  • Document conventions and edge-case decisions

Required
  • Recent graduate with a degree in CS, EE, AI/ML, or related field
  • Working knowledge of Python and common CV libraries (NumPy, OpenCV)
  • Attention to detail and patience for precision work

Nice to Have
  • Hands-on experience with YOLO
  • Familiarity with PyTorch, segmentation masks, or model-assisted labeling workflows

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About BrightAI

Sourced by ZipRecruiter

Industry

Software development

Company size

11 - 50 Employees

Headquarters location

San Francisco, CA, US

Year founded

2019