Video Annotator

**About Turing:
**Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.

Role Overview

We're looking for detail-oriented video annotators to support a shot boundary detection project. Annotators will watch video clips, identify where shots begin and end, classify transition types (cuts, fades, dissolves, wipes), and group shots into scene buckets with category labels.

Job Responsibilities

• Watch video clips frame-by-frame and identify all shot boundaries
• Create a "Shot Card" for each shot, capturing start/end frames
• Identify and label the shot transition type and subtype (cut, fade, dissolve, wipe, etc.)
• Group shot cards into scene buckets based on narrative/event continuity
• Classify each video clip and scene bucket by category (e.g., TV-Streaming/Drama, Education/Documentary, Gaming/Sci-Fi, Podcast/Lifestyle)
• Maintain consistency and accuracy across a high volume of annotations
• Follow detailed labeling guidelines and flag edge cases for review

Job Requirements

• 1+ year of experience in video/film editing, content creation, or video production
• Strong understanding of shot composition, editing techniques, and transition types
• Sharp attention to detail and ability to distinguish subtle visual cues (e.g., panning/zooming vs. an actual shot change)
• Comfortable working with annotation tools and following structured labeling workflows
• Ability to work independently and meet quality/throughput targets
• Good written communication for documenting edge cases or ambiguous calls
• Nice to Have:

Nice to have Qualification:

• Background in film studies, cinematography, or media production
• Prior experience with data annotation or labeling projects
• Familiarity with different genres (drama, documentary, gaming, podcast/lifestyle content)

Benefits

• Opportunity to work on cutting-edge AI projects.
• Competitive compensation.
• Flexible working hours and remote work environment.

Application Process

• Shortlisted candidates will complete an assessment.
• Once the assessment is cleared, candidates can start.