Computer Vision Data Annotation Specialist

Role Title: Computer Vision Data Annotation Specialist

Role Type: Contractor

Location: Northern America, Latin America, Europe

micro1 is engaging Computer Vision Data Annotation Specialists to contribute to a project advancing hand tracking and pose estimation technologies. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

Scope of Work

1. Review and annotate images and video frames, focusing on detailed hand pose landmarks including wrists, finger joints, and fingertips.

2. Validate the accurate identification of left and right hands in diverse scenarios.

3. Detect, flag, and document edge cases such as occlusion, motion blur, gloves, multiple hands, and low-light conditions.

4. Apply thorough annotation guidelines and quality rubrics to ensure data reliability and consistency.

5. Maintain high accuracy and productivity when managing large datasets for computer vision training.

6. Report ambiguous, challenging, or unclear cases to project leads for clarification and guidance.

7. Perform quality assurance reviews on previously annotated data as needed.

Preferred Qualifications

1. Proven experience in image or video annotation for machine learning or AI projects.

2. Proficiency with annotation platforms.

3. Strong attention to detail, spatial reasoning, and ability to follow intricate visual guidelines.

4. Basic familiarity with computer vision concepts such as landmarks, bounding boxes, confidence scores, and ground truth labeling.

5. Experience with hand or human pose estimation datasets, or frameworks.

6. Background working on gesture recognition, sign language, AR/VR hand-tracking, or related datasets.

7. Excellent written and verbal English communication skills for documenting findings and collaborating remotely.

Originally posted on Himalayas