Visual Data Labeler — Images & Video (15–20 hrs/wk)

About OpenTrain

OpenTrain is the #1 platform for building careers in AI training and data labeling. We connect skilled contributors with long-term projects that shape how real-world AI systems behave.

OpenTrain AI is the hiring and contracting organization for this role. We focus on reliable, remote work that helps people grow practical skills in the fast-growing field of AI training.

About AI Training and Visual Annotation

AI training (data labeling/annotation) is the human work behind modern computer vision systems. Accurate image and video annotations—bounding boxes, polygons, keypoints, cuboids, and classifications—are how models learn to see and understand the world.

This role places you directly on the front line of computer vision development: your annotations improve model performance and safety across products that rely on visual understanding.

The Role

We are hiring experienced data labelers for a long-term, ongoing visual annotation project. Work is contractor, part-time, and flexible: set your own hours while committing to 15–20 hours per week and delivering assigned tasks on time.

This position requires annotating images and videos using a range of label types and tools and maintaining a consistently high level of quality over months of work.

• Employment type: Contractor, part-time
• Weekly commitment: 15–20 hours per week, flexible schedule
• Location requirement: Must be located in Canada or the USA
• Pay: $14 USD per hour

What You'll Do

Daily work involves detailed visual annotation tasks across image and video datasets. You will follow project guidelines to create training data that machine learning teams can trust.

• Draw and verify bounding boxes, polygons, and cuboids for objects and scenes
• Label object classes and perform frame-by-frame object detection annotation
• Mark keypoints/landmarks on people, objects, or parts as specified
• Apply classification labels to images or video clips according to schema
• Follow style guides, flag ambiguous or low-quality media, and propose clarifying questions when needed

Qualifications

Candidates must have a proven track record in image and video annotation and be comfortable working independently to meet quality and schedule expectations.

• 2–3+ years of hands-on experience with image and video data labeling
• Proven experience with bounding boxes, polygon annotations, cuboids, keypoints, classification, and object detection
• Familiarity with annotation tools such as Labelbox, CVAT, VGG Image Annotator, or similar platforms
• Strong attention to detail and a history of reliable, consistent performance on long-term projects
• Good communication skills for collaboration and reporting
• Ability to manage time effectively and work independently
• Must be located in Canada or the USA and able to commit 15–20 hours per week

Who Should Apply

This opportunity is ideal for experienced computer vision annotators, freelancers, and contractors seeking steady, part-time work with predictable weekly hours.

Apply if you value long-term projects, have a portfolio or past work examples in image/video annotation, and can commit to consistent, high-quality output.

How to Apply & Interview Prep

When applying, include your resume, a short summary of your annotation experience, and examples or a portfolio of image/video projects you’ve worked on. Tell us which annotation tools you used and describe the types of visual tasks you completed.

During screening you should be prepared to describe specific image/video annotation projects you’ve completed, the tools you used, and how you ensured label quality and consistency.

• Include: location (Canada or USA), availability for 15–20 hrs/week, and confirmation you can work as a contractor
• List annotation tools and workflows you’re proficient with and provide links or screenshots of past work if available
• Be ready to discuss quality control steps you take and examples of challenging annotation scenarios you resolved