Experience: 3+ years
Job Type: Full-time (Contractual / Freelancing)
Location: Remote
Required Skills: Video Annotation, Attention to Detail, Data Labeling, Video Annotation Tools, Time Management
Job Summary:
We are engaging Senior AI Trainers to collaborate on a customer-driven project enhancing AI system accuracy through expert-level video annotation and data labeling. 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.
Key Responsibilities:
- Review video footage of robotic arms executing assigned tasks, identifying key actions and outcomes with precision.
- Apply detailed grading guidelines to accurately tag and annotate events, providing structured observations that improve model performance.
- Mark precise timestamps for the start and end of key actions, transitions, and outcomes, ensuring frame-accurate segmentation of each video session.
- Verify timestamp accuracy and alignment across annotations, correcting drift or inconsistencies between labeled events and the underlying footage.
- Utilize video annotation tools and platforms to record findings and submit annotated datasets in alignment with project standards and milestones.
- Collaborate with project trainers and contributors to resolve ambiguities, refine guidelines, and ensure annotation consistency across the team.
- Participate in ongoing quality reviews, incorporating feedback to maintain rigorous annotation standards.
Required Skills and Qualifications:
- Exceptional attention to detail and accuracy in reviewing and tagging visual data.
- Strong written and verbal communication skills for effective collaboration, reporting, and timely updates on progress and challenges.
- Demonstrated time management and self-organization abilities for independent, remote project participation.
- Analytical and problem-solving mindset, with a proactive approach to resolving annotation challenges.
Preferred Qualifications:
- Proven experience with video annotation, data labeling, or similar data-centric annotation projects.
- Familiarity with video annotation tools and software platforms, including timeline-based interfaces for timestamping and event segmentation.
- Experience with frame-level or timecode-based annotation (eg, marking event boundaries, working with frame rates, or reviewing footage frame by frame).
- Background in AI training, machine learning data preparation, or robotics projects (strongly preferred).