Hand Landmark Annotation Artist

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this role and the #1 platform for finding and building careers in AI training and data labeling. OpenTrain helps contributors discover specialized projects, build a professional AI-training profile, and grow in a fast-moving field shaping how modern AI systems work.

About AI Training Work

AI training is the human side of building artificial intelligence. Contributors prepare and review examples—such as labeled images and videos—so AI models can recognize patterns, interpret visual information, and respond more effectively.

• Work remotely from anywhere with a computer or phone and an internet connection.
• Build practical experience contributing to cutting-edge AI systems.
• Use your existing subject-matter expertise without needing prior AI-training experience.

The Role

OpenTrain AI is seeking a Hand Landmark Annotation Artist for a specialized AI-training project. You will annotate hand and finger landmarks in image and video data using MediaPipe-style hand topology, applying your understanding of hand anatomy, motion, and complex poses.

This is a remote, part-time contractor position open worldwide. The role is listed as entry level because prior AI-training experience is not required; expertise in hand anatomy, character animation, or hand biomechanics is the relevant foundation.

• Employment type: Contractor and part time
• Time requirement: 20+ hours per week
• Work location: Worldwide and fully remote
• Working language: English
• Compensation: $15–$80 per hour

What You'll Do

You will create precise, consistent landmark annotations while following detailed protocols and tolerance thresholds. The work requires careful visual reasoning across varied hand poses, orientations, perspectives, and interactions with objects.

• Annotate hand and finger landmarks or keypoints using MediaPipe-style hand topology.
• Mark the wrist, MCP, PIP, DIP, fingertips, and thumb-specific joints, including the CMC, MCP, IP, and thumb tip.
• Precisely place landmarks according to defined protocols and tolerance thresholds.
• Infer and annotate partially occluded or visually challenging joints.
• Interpret complex hand positions, orientations, perspectives, and object interactions.
• Review visual feedback, identify deviations, and make targeted corrections.
• Maintain consistent annotation quality across image and video data at scale.

Requirements

You should be comfortable analyzing hand poses and working carefully with visual data. Detailed annotation guidelines must be followed consistently, and strong attention to detail is essential.

• Expertise in hand anatomy and pose understanding.
• Strong attention to detail and visual reasoning ability.
• Ability to follow detailed annotation protocols and guidelines.
• Comfort working with image and video data.
• No prior AI-training experience required.

Helpful Background

Experience in related visual or motion-focused fields can help you understand hand structure, movement, and landmark systems. These backgrounds are helpful but are not listed as required qualifications.

• Character animation
• 3D modeling
• Motion capture
• Familiarity with MediaPipe hand topology or similar landmark systems
• Experience with annotation tools

Why This Work Matters

Your annotations will help AI models interpret hand gestures and poses more accurately. This foundational work can support more natural human-computer interaction, including sign language recognition, virtual reality, and augmented reality applications.