Image & Video Data Labeler — Latin America (15–20 hrs/wk)

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. Creating an OpenTrain account is free, and the platform connects contributors with steady annotation projects while helping them grow skills and a professional profile in this fast-growing industry.

About AI training and this work

AI training (also called data labeling or annotation) is the human work that teaches machine learning models how to see and interpret images and video. Contributors annotate visual data with bounding boxes, polygons, keypoints, segmentation masks, labels and more — work that directly shapes how modern computer-vision systems behave.

This role is remote and flexible, a common format in AI training: part-time, steady assignments you can fit around other commitments while gaining hands-on experience in computer-vision annotation.

The role — what we’re hiring for

We’re hiring experienced image and video data labelers based in South America or Latin America to join a long-term project. You will work as a contractor for 15–20 hours per week with flexible scheduling, delivering consistent, high-quality annotations on an ongoing basis.

• Commitment: 15–20 hours per week (part-time, long-term project).
• Location: Must be located in South America or Latin America (remote).
• Employment type: Contractor, part-time.
• Pay: $3.75 USD per hour (applicants are asked to consider long-term potential when proposing competitive rates).
• Data: Image and video datasets for computer-vision tasks.

What you’ll do day-to-day

Tasks are practical, annotation-focused, and quality-driven. You’ll follow detailed labeling guidelines and use common annotation tools to produce data that training teams depend on.

• Create bounding boxes and object-detection annotations across images and video frames.
• Perform polygon and segmentation annotations for precise object outlines.
• Label object classes and perform classification tasks.
• Place point keypoints and annotate pose/landmarks where required.
• Work on video frame sequences, ensuring temporal consistency and tracking where needed.
• Perform quality checks and correct annotations as requested to meet accuracy targets.

Requirements

You must be a reliable, detail-oriented annotator with hands-on experience and the ability to work independently on a recurring schedule.

• Experience: 2–3+ years of image/video data labeling experience (bounding boxes, polygons, segmentation, keypoints, classification).
• Tools: Proficiency with annotation platforms and tools (examples include common industry tools such as Labelbox, CVAT, VGG Image Annotator or similar).
• Attention to detail: High accuracy and consistent quality in annotations.
• Work style: Able to manage time independently and meet deadlines on a recurring weekly schedule.
• Communication: Clear, timely communication for collaboration and reporting.
• Availability: Willingness to commit to 15–20 hours per week.
• Pricing: Able to offer competitive, consistent rates and consider long-term engagement when proposing pricing.

Who should apply

This role is a fit for intermediate-level computer-vision annotators and experienced freelance labelers in Latin America who want steady, part-time work. If you have a proven track record on visual annotation projects and prefer flexible scheduling with regular weekly hours, apply.

• Experienced visual annotators seeking long-term, part-time contractor work.
• Freelancers who deliver high-quality, reliable annotations and want steady weekly hours.
• Candidates based in South America or Latin America with the required tool experience.

How to apply and what we’ll ask

Create a free OpenTrain account to apply. Submit your resume, a brief description of your relevant image/video projects, and examples or screenshots of previous annotations if available. Include your hourly rate (note posted pay is $3.75/hr) and your weekly availability.

During screening we’ll ask about specific image/video annotation projects you’ve completed, the annotation tools you’ve used, and your approach to maintaining quality and consistency. Interviewers will focus on visual annotation experience — text-only labeling is not relevant for this role.

• Application materials: resume, sample annotations or portfolio, hourly rate, and availability.
• Interview topics: project examples, tools used, typical throughput and accuracy, and how you handle edge cases.
• Next steps: qualified applicants will be invited to a short skills check or sample task to verify accuracy and speed.