Senior AI Trainer, Remote - Contract

Role Title: Senior AI Trainer Role Type: Contractor Location: Remote Required Skills - Video Annotation - Attention to Detail - Data Labeling - Video Annotation Tools - Time Management 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 (e.g., 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). Originally posted on Himalayas